United States                  WJt-600 /2-'87$02
            Environmental Protection                      -'->
            *Be"cv  .                  November 198T%
&EPA     Research and
            Development
           EVALUATION OF

           THE EFFECTIVENESS OF

           CHEMICAL DUST SUPPRESSANTS

           ON UNPAVED ROADS
           Prepared for
           EPA Region 5
           Prepared by
           Air and Energy Engineering Research
           Laboratory
           Research Triangle Park NC 27711

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                                            EPA-600/2-87-102
                                            November 1987
EVALUATION OF THE EFFECTIVENESS OF CHEMICAL DUST
         SUPPRESSANTS ON UNPAVED ROADS
                       By
       G. E. Muleski and C.  Cowherd,  Jr.
           Midwest Research  Institute
              425 Volker Boulevard
          Kansas City,  Missouri   64110
                  Funded By:

            LTV Steel Company,  Inc.
      Penalty Credit Project  5200-868236
              EPA Project  Officer;

              Robert  C.  McCrillis
 Air and Energy Engineering  Research Laboratory
 Research Triangle Park, North  Carolina  27711
                 Prepared For;
     U, S. Environmental Protection Agency
       Office of Research and Development
             Washington,  DC  20460

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                                  PREFACE
     This report was prepared by Midwest Research Institute (MRI) under LTV
Steel Company,  Inc.  (formerly,  Jones and Laugh!in Steel Corporation) Pur-
chase Order No.  5200-868236.   Tht penalty credit project described herein
was directed  by the U.S.  Environmental Protection Agency, Air and Energy
Engineering Research Laboratory     (Robert C. McCrillis, Project Officer).
All work was  performed in MRI's Air Quality  Assessment Section     (John
Kinsey, Head).

     The authors of this report are     Gregory E. Muleski, Project Leader,
and     Chatten Cowherd, Jr.   Field sampling was conducted under the direc-
tion of     Frank  Pendleton and     Muleski with  assistance from     David
Griffin,     Julia Hoffmeister,     Phillip Englehart, and     Scott Smith.
Additional  laboratory analysis was performed by     Stephen Cummins.
                                     ii

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                                 CONTENTS
                                                                      Page
Preface.	   11
Figures	-•  •   iv
Tables	    v
Summary and Conclusions. .  	 .....   vi

     1.0  Introduction	    1
               1.1  Program objectives 	    2
               1.2  Report structure .... 	    2
     2.0  Selection of Control Measures, Test Sites, Study
            Design, and Description of test Methodology	    3
               2.1  Characterization of unpaved road traffic ....    3
               2.2  Control measure selection	    7
               2.3  Test site selection	    7
               2.4  Selection of study design	   11
               2.5  Quality assurance	   14
               2.6  Air sampling equipment and technique 	   14
               2.7  Emission testing procedure 	   18
               2.8  Aggregate material sampling and analysis ....   29
               2.9  Auxiliary equipment and samples	   29
     3.0  Chronology of the Field Testing Program and Test
            Results	   33
               3.1  Modifications to test plan	   33
               3.2  Source description	,	   34
               3.3  Control applications ...... 	   37
               3.4  Results of the exposure profiling tests	   39
     4.0  Control Efficiencies and Cost Effectiveness Values ....   58
               4,1  Comparisons involving only one chemical	   59
               4.2  Average control efficiency . 	   60
               4.3  Interchemical comparisons	   60
               4.4  Relative cost-effectiveness of the
                      suppressants evaluated 	   63
               4.5  Examination of alternative indicators of
                      control performance	   66
     5.0  Control Performance Model Development	   69
               5.1  Objectives of the average control performance
                      model.  ........ 	   69
               5.2  Review of previous studies 	   70
               5.3  Average control model for petroleum resins  ...   73
     6.0  References	   76
     7.0  Glossary	   78
     8.0  English to Metric Unit Conversion Table	   81
                                     m

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                                  FIGURES


Number                                                                Page

 SC-1     Average control efficiency as a function of time over
            30 days	viii
 2-1      Copy of IN-TECH summary data of vehicle miles traveled
            in iron and steel  industry	     4
 2-2      Copy of IN-TECH summary data of iron and steel unpaved
            road traffic by vehicle type	     5
 2-3      Copy of IN-TECH summary data of average weights for
            vehicle types on iron and steel  unpaved roads	     6
 2-4      MRI exposure profiler	    16
 2-5      Cyclone preseparator/cascade intpactor combination.  ....    17
 3-1      Test site at plant AP	    35
 3-2      Test site at plant AQ	    36
 3-3      Variation of surface material properties (before control)
            over test sections (see text for mean values)	    40
 3-4      Cumulative rainfall  and chronology of events at
            plant AQ	    45
 4-1      Average control efficiency as a function of time over
            30 days	    61
 4-2      Relationship between controlled PM10 emission factors
            and silt loading.   Arrows indicate chronology of
            testing	    68
 5-1      Average control performance model  for petroleum resins .  .    74
                                     IV

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                                  TABLES


Number                                                                Page

 2-1      Unpaved Road Dust Control  Survey Results 	     8
 2-2      Dust Suppressants Recently Used or Considered for
            Evaluation	    10
 2-3      Air Sampling Equipment	    15
 2-4      Quality Assurance Procedures for Sampling Media	    19
 2*5      Quality Assurance Procedures for Sampling Flow Rates ...    20
 2-6      Quality Assurance Procedures for Sampling Equipment. ...    21
 2-7      Criteria for Suspending or Terminating an Exposure
            Profiling Test	    22
 2-8      Moisture Analysis Procedures 	    30
 2-9      Silt Analysis Procedures	    31
 3-1      Application Parameters - Plant AP	    38
 3-2      Application Parameters - Plant AQ	    38
 3-3      Test Site Parameters - Plant AP	    41
 3-4      Test Site Parameters - Plant AQ	    42
 3-5      Representative Concentrations (ug/m3) - Plant AP 	    46
 3-6      Representative TP Concentrations (ug/m3) - Plant AQ. .  .  .    47
 3-7      Isokinetic Correction Parameters - Plant AP	    48
 3-8      Isokinetic Correction Parameters - Plant AQ	    49
 3-9      Aerodynamic Particle Size Data - Plant AP	    50
 3-10     Aerodynamic Particle Size Data - Plant AQ	    51
 3-11     Plume Sampling Data - Plant AP	    53
 3-12     Plume Sampling Data - Plant AQ	    54
 3-13     Surface Properties and Emission Factors - Plant AP  . .  .  .    55
 3-14     Surface Properties and Emission Factors - Plant AQ  . .  .  .    56
 5-1      Summary of Major Unpaved Road Control Efficiency Tests
            Performed at Iron and Steel Plants	    71
 5-2      Average Control Efficiency from Tests of Petroleum
            Resins in the Iron and Steel Industry	    72

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                          SUMMARY AND CONCLUSIONS


     The purpose of this study was to obtain data characterizing the average
control performance of dust suppressants commonly used by the iron and steel
industry to mitigate  particulate emissions from unpaved roads.   Vehicular
traffic on unpaved roads has been estimated to contribute more than half of
the suspended  particulate emissions from  open  sources in the  industry.

     Control efficiency values were  determined not only for  total  particu-
late (TP),  but  also  for particles less than 15 urn in aerodynamic diameter
(inhalable particulate, IP), less than 10 urn in aerodynamic diameter (PM10),
and less than  2,5  urn  in aerodynamic diameter (fine particulate, FP),   The
study focused on PMio  control performance  of dust suppressants  in  particu-
lar, because this size fraction is anticipated to form the basis of any re-
vised National  Ambient Air Quality Standard for particulate matter.

     In order to make the control performance test results as useful as pos-
sible to the industry, unpaved road vehicular traffic characteristics and
dust control techniques  used  in the industry were surveyed  early in the
study.   Subsequently  these  results  formed the basis  for the design of the
field testing program so that commonly used suppressants could be evaluated
under service conditions  representative of typical iron and  steel  industry
unpaved roads.

     The exposure  profiling method developed by  MRI was the  technique  uti-
lized to measure uncontrolled and controlled emission factors for vehicular
traffic on unpaved roads.   Exposure profiling of roadway emissions involves
direct  isokinetic  measurement  of the total passage of open dust emissions
approximately 5 m downwind of the edge of the road by means of simultaneous
sampling at four points distributed vertically over the effective height of
the dust plume.  Downwind particle size distributions were measured using
cyclone precollectors  followed by parallel slot  cascade impactors.  Upwind
particle size distributions were also  determined using  impaction.   A total
of 64 tests of controlled and uncontrolled particulate emissions from vehic-
ular traffic on  unpaved roads were conducted at  two iron  and steel  plants.

     Five  chemical  dust  suppressants  were evaluated  during the study:

          Petro Tac, an emulsified asphalt

          Coherexf, a petroleum resin

          Soil-Sement, an acrylic cement

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          Generic 2 (QS),  a generic petroleum resin product developed at the
          Mellon Institute

          liquidow ,  a salt (calcium chloride)

All products, with the  exception of Generic, have  been  used in iron and
steel  plants.   In addition, industry personnel  have expressed considerable
interest in the use of Generic.

     These suppressants were applied under the direction of MRI personnel in
quantities that generally spin the range of common practice in the industry,
manufacturers1  recommendations,  and previous field evaluations.   Control ef-
ficiency measurements were  made  over periods up to 70 days after applica-
tion,  although  the main  averaging  period  of interest was approximately
1 month.  The latter  is representative  of  time  periods between  control  ap-
plications in the industry.

     Average control  efficiencies over the first 30 days for specific parti-
cle size  ranges  are presented in  Figure SC-1.   Note that code letters  (ex-
plained in the text)  have been assigned to the various dust suppressants in
order to  discourage selective citation  of  test  results.  It  is  recommended
that the report taken as a whole be used as a basis for decisions regarding
dust control programs  rather  than any  one  data set taken  independently,

     All chemicals tested exhibited average control efficiencies of approxi-
mately  50%  or more  over the first 30 days after application.  These tests
were conducted using application and traffic parameters that may be consid-
ered typical in  the  iron and steel industry.  Note that while the control
provided by some suppressants showed significant temporal decay, others ex-
hibited a relatively constant level of control over the time period.

     Statistical analyses  of  the data  indicate that reapplication results
in a significantly higher level  of control  and that  only  one suppressant
exhibited significant  differences  in control between the various particle
size fractions.   Comparisons between the control efficiencies for different
chemicals indicate that there were relatively few suppressant/size fraction
combinations which could be considered  significant at the 5% level.

     Comparison  of the  relative  cost-effectiveness reveals only  a slight
variation between the suppressants other than calcium chloride.   In terms of
cost-effectiveness, the salt did not compare favorably with the other prod-
ucts; however, this is at least a partial  result of the abnormally high pre-
cipitation during the field exercise.

     Several road  surface material  properties were discussed as  possible
indicators  of control  performance.   While reasonably strong relationships
between silt  loading  and control were  found for some of the suppressants,
the clustered nature  of the entire  data set precluded development of  a re-
liable  performance indicator.   However, the data  suggest  that  the indus-
trial paved  road emission factor equation  may  be  used to conservatively
overestimate emissions  from controlled  unpaved  roads.

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                                             AQ-/ +o  -&
               10
                                           IO
                             AFTER  APPI./CAT/CM
Figure SC-1.  Average control efficiency as a function of time  over 30 days.
                               vm

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     Finally, results of  previous  tests were combined with  data  from  the
present study to develop an average control performance model for petroleum
resins.   The model was designed to meet typical needs in the iron and steel
industry in terms of averaging periods and service environments.
                                     IX

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                                SECTION 1.0

                               INTRODUCTION


     Numerous prior studies  of  the iron and  steel  industry1 4  have  shown
that open  dust  sources (such as vehicular  traffic  on paved and  unpaved
roads,  material  handling and wind erosion) merit prime consideration in the
development of particulate emission control strategies.   This conclusion has
been based on (a)  industry-wide comparisons between  uncontrolled  emissions
from open dust sources, and (b)  typically controlled fugitive emissions from
major process sources  such  as steel-making furnaces, blast furnaces, coke
ovens,  and sinter  machines.   In addition, preliminary cost-effectiveness
(dollars expended  per  unit mass of reduced  particulate emissions)  analysis
of promising control options  for open  dust  sources  has indicated  that  con-
trol of these sources might result in significantly improved air quality at
a lower cost compared to the control  of process sources.

     Of open dust sources, vehicular traffic on paved and unpaved roads gen-
erally account  for the vast majority of particulate emissions in the iron
and steel industry.  For the 1970's,  unpaved surfaces were estimated to ac-
count for roughly 70% of open source particulate emissions in the industry.2
By the early 1980's the contribution was considerably smaller.   This reduc-
tion was due to  implementation  of dust control  programs which,  in  addition
to chemical treatment  of  unpaved roads,  included paving numerous  roads  and
using shuttle buses  to reduce emissions from employees commuting to their
work stations.

     Some unpaved roads in the iron and steel  industry are, by their nature,
not suitable for paving.  These roads are normally used by very heavy vehi-
cles or may be subjected to considerable spillage.   Because of the additional
maintenance  costs  associated with a paved  road under this type of service
environment, emissions from these roads generally are controlled with regu-
lar reapplications of chemical treatments.

     Besides water, petroleum resins  (such as  Coherex®) have historically
been the products  most widely used in the industry; however, considerable
interest has been shown at both the plant and corporate level in alternative
chemical dust suppressants.   As a result of this continued interest, several
new dust suppressants  have  been introduced recently.  These have  included
asphalt emulsions, acrylics,  salts, and adhesives.   In addition, the generic
petroleum resin formulations  developed at the Mellon Institute with  funding
from the American  Iron and  Steel Institute  (AISI)  have gained considerable
attention.   These generic suppressants were designed to be produced  on-site
at iron and steel plants.5

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1.1  PROGRAM OBJECTIVES

     The overall objective of this study was to provide data  that document
the reduction of participate  emissions (in several particle  size ranges)
generated by vehicular traffic on representative unpaved  roads  in the  iron
and steel industry  following  control  application.   The data  were used to
provide average control efficiencies  for common road dust suppressants^ over
ranges of averaging  periods  and  application parameters that  span typical
values used  in  the  iron  and steel industry.   Information on  this type is
valuable to  both industry and regulatory personnel  in developing and moni-
toring dust control  programs.

     In addition,  there were several  secondary objectives which largely sup-
ported the primary  objective  stated  above.  These included:  (a) a survey
of current and  projected  industry practices in unpaved road dust control;
(b) characterization of traffic on unpaved roads in the industry; (c)  col-
lection of cost data to develop relative cost-effectiveness values  for the
suppressants evaluated; (d)  examination of less expensive measures to moni-
tor control  performance;  and  (e)  analysis  of the current previous studies
in order to develop  a model  to estimate control performance.

1.2  REPORT STRUCTURE

     The report is  structured  as  follows;   (a) Section 2.0 focuses on the
methodology  used to quantify road dust controls used in the iron and steel
industry; (b) Section 3.0 presents and discusses the results of source test-
ing by exposure profiling; (c) Section 4.0 discusses control efficiency and
cost-effectiveness  values for the dust suppressants evaluated; and (d) Sec-
tion 5.0 discusses  a model developed  to estimate average control performance
as a function of application parameters.   Sections 6.0 and 7.0 presents the
references and a glossary, respectively.                              i

     This report contains both metric and English units.   In the text, most
numbers are generally reported in metric units with English units in paren-
theses.  For numbers commonly expressed in metric units in the air pollution
field  (e.g., particle  size  in urn, density  in  g/cm3, and  concentration in
Mg/m3), no English  equivalent  is  given.   A conversion table  is given as
Section 8.0.

     Finally, the particle size ranges used in this report are:

       TP      Total airborne particulate matter.

       IP      Inhalable particulate  matter consisting of particles smaller
               than IS pm in aerodynamic diameter.                    :

       PM10    Particulate matter  consisting  of  particles  smaller than
               10 urn in aerodynamic diameter.                         !

       FP      Fine particulate matter consisting of particles smaller than
               2.5 (jm in aerodynamic diameter.

Particular attention  is paid to the PM10 size  fraction,  in  anticipation of
possible revision of National Ambient Air Quality Standards for particulate
matter.
                                   2

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                                SECTION 2.0

         SELECTION OF CONTROL MEASURES, TEST SITES, STUDY DESIGN,
                    AND DESCRIPTION OF TEST METHODOLOGY
     This section  describes how specific  unpaved  road dust suppressants
were  selected  for testing and  how  the test conditions were determined.
Also, the selection  criteria for test sites and the  study  design  are  re-
viewed.   Finally the  detailed  test methodology, including air and surface
material sampling and analysis, is described.

2.1  CHARACTERIZATION OF UNPAVED ROAD TRAFFIC

     During recent years,  the  iron and steel industry has paved many pre-
viously unpaved  roads  used  primarily  by  light-duty vehicles  (e.g., automo-
biles, pickup  trucks),  while roads used by heavy-duty trucks have largely
remained unpaved.  In  addition, a good deal  of  light  duty traffic  has  been
eliminated by  employee  bussing programs.   In order to design the  testing
program so that  the  test results would  be as useful  as possible,  a  study
was conducted  to  determine  the relative importance of light-duty vehicles
on unpaved roads in the industry.

     IN-TECH of  Pittsburgh,  Pennsylvania was retained to provide  summary
data collected during  traffic  studies of  paved and unpaved  roads  at nine
different steel  plants  east of the  Mississippi  River.  These data  are  pre-
sented in Figures 2-1, 2-2, and 2-3.

     These data  show  that,  while autos generally account  for a  large frac-
tion of the total number of vehicle miles  on unpaved roads,  the average ve-
hicle weight mile is substantially  larger  than that for a car.   For  the nine
plants, an average weight of approximately 10 tons was found, and over half
of the  daily  mileage was due to vehicles  weighing between 10 and 30 tons.

     Although  paved  roads  generally experience a  greater volume (approxi-
mately  six times,  on the average)  of  traffic than do  unpaved roads, it is
important to  note  that unpaved roads  are  usually  responsible for  more SP
emissions.  This  statement  is  based on the fact that  the leading term for
the AP-42 unpaved  road emission factor equation is about 60 times greater
than that for  industrial paved roads.6  Because unpaved roads generally are
used  by  much  heavier vehicles, it  is  apparent  that unpaved roads  are  the
more  important source.  Furthermore, comparison of the leading terms for the
PM10  equations  shows  that unpaved  roads contribute emissions in this  size
range at a level comparable to paved roads.

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SUIWRY TABLE
TOTAL MILES OF PAVED

AND DAILY VEHICLE
MILES OF
BY PUNT I.D. AND TYPE
PLANT 1.0.

1
2
3
4
5
6
7
8
9
MILES OF
UNPAVED
3.62
4.59
1.40
9. SO
1,57
1,4
1.8
10.717
11.51
ROADWAY
PAVED
1.02
0.82
3.35
0.37
0.18
8.2
8.4
14.815
1.97
1
ROADWAY
TRAVEL (V.M.T.)
OF ROADWAY
DAILY
UNPAVED
262.00
115.20
138.50
3675.00'
154.30
384.02
438.60
436.00
1877.30




V.M.T.
PAVED
299.08
4462.40
839.50 ,'
124.00
131.70 :
7750.98
5213.00
9800.00
1105.70
Figure 2-1.   Copy of IN-TECH summary data of vehicle miles traveled In
               iron and steel industry.                              '

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SUMMARY TABLE 2
TOTAL DAILY VEHICLE MILES OF TRAVEL FOR UNPAVED ROADWAYS

PLANT 1.0. AUTOS
1 1IB.6
I 43.5
3 641.2

4 25H.33
5 19.10
6 191.6
7 148.70
B 106.2
9 815.7
* K-Mflfi
** SLAfiPOT
DV PLANT l.D. AND VEHICLE
TRUCKS (AXIES)
23456789
18.9 0.24 0.24 4.5
1B.1 30.2 22.2
39.66 132.96

162.96 79.3 47.3 171.6* 1 10.56
27.5 20.3 10.2 48.9
87.5 27.6 B.O 9,5
5.0 128.0 B5.0 19.2
2.9 1.2 5.8 243.5 2.7 0.2
29.60 541.0 5.0


CLASSIFICATION
10 11 EUCLID PLANT
EQUIPMENT
84.0 35.52
1.2
7.0 55.78
61.9*
121.0 443.71
2B.3
60.0
52.7
3.B 2.6 68.10
306.4 85.4
10.4**



TOTAL
262.0
115.20

933.50
3675.00
154.30
384.02
438.60
436.00
1877.3


Figure 2-2,   Copy of IN-TECH summary data of iron and steel  unpaved road traffic
               by vehicle type.

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SUMMARY TABLE 3
AVERAGE VEHICLE HEIGHTS IN THOUSANDS OF
FOR VEHICLES USING WAVED ROADS
BY PLANT 1.0. AMD VEHICLE CLASSIFICATION
PLANT 1.0. AUTOS 2
1
2
3
4
5
6
7
8
9

3.5
3.5
3.5
3.5
3.5
3.5
3.5
3.5
3.5
* K-MA6
** SLAG POT
0 Average of
36.0
37.5
31,5
34.5
32.5
27.0
30.6
33.0
33.0
3 4
23.0 47.0
23.0 48.5

23.0 47.5
23.0 47.0
23.0 53.5
23.0 49.7
38.0° 44.0"
37.5°
loaded and unloaded
TRUCKS (AXLES)
56789
49.2
52.5
48.9
46.5 51.5
51.5
52.5
50.6
48.0 52.0 62.0
53.0 56.0
weight
10 11 EUCLID PLANT EQUIPMENT
00.0 36.5
SI. 5 36.0
80.0 28.0
190.00 *
00.0 34.3
33.5
35.0
32.8
72.0 73.0 3i.O
76.0 37.5
145.00 **

Figure 2-3.   Copy of IN-TECH summary data of average weights for vehicle types on iron
               and steel unpaved roads.

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     In summary,  most vehicle-generated road dust in the iron and steel in-
dustry appears to be  due to unpaved roads, and most of this contribution
arises from medium- to. heavy-duty vehicles.  As more roads become paved in
the industry, the relative  importance  of unpaved road dust emissions  may
decline,  but the importance of reducing emissions from medium to heavy ve-
hicles on unpaved roads will remain.   This is the type of traffic considered
in the field testing program.

2.2  CONTROL MEASURE SELECTION

     Historically,  the most widely used control measure for unpaved  roads,
besides watering, has  been  Coherex® (a petroleum resin).  However, because
of the sharp  rise  in  prices of petroleum-based products over the past de-
cade,  the iron and  steel  industry has  expressed interest in less expensive,
alternative chemical controls.   These  control  measures may beeither pet-
roleum resin products  similar  to Coherex® (such as Resinex 6CP) but with
potentially lower delivery  costs,  or  products of another nature (such as
asphalt emulsions,  salts, or adhesives).

     In order to assess  interest in chemical control of road dust within
the industry, a  survey of corporate officials was conducted.   Additional
information was obtained  during  site  surveys.   The results (based largely
on data from 1984 control programs) are shown in Table 2-1.   As can be seen,
petroleum resins represented the most widely used dust suppressants  in the
industry at the end of 1984.  In fact,  only one of the five surveyed corpo-
rations did not  use  this type of product during 1984.  Asphalt emulsions
(e.g., Petro Tac) were the  next most widely used suppressant type in  the
industry.

     To further characterize the changing nature of dust suppressant use in
the iron and steel  industry, the survey also contained questions about past
control programs and  any plans to evaluate chemicals in the future.   The
replies are presented  as Table 2-2.   In addition to the interest shown in
Dustaside® and Soil  Sement,  considerable interest in generic petroleum resin
was expressed.   These  generic formulations were developed at  the  Mellon
Institute with funding from the  American Iron and Steel  Institute (AISI).

     Upon completion of  the survey,  five products were selected for field
testing — Coherex®, Petro Tac, Soil  Sement, Dustaside®,  and Generic 2 (QS).
Based on  the  results  of the survey, these products largely characterized
current and projected practice in the iron and steel industry.

2.3  TEST SITE SELECTION

     Because the scope of work for this study required that test sites be
chosen from LTV's Aliquippa,  Cleveland and Indiana Harbor works, each of
these plants was surveyed by MRI personnel.  Candidate sites were examined
using criteria of:   (a) road length and orientation with respect to prevail-
ing winds; (b) traffic mix and rate; (c) upwind/downwind flow obstructions;
(d) general meteorology  such  as  mean  wind speed, prevailing direction and
frequency of precipitation; (e)  availability of  chemical dust  suppressants
and application equipment; and (f) proximity to MRI.

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                                    TABLE 2-1.  UNPAVED ROAD DUST CONTROL SURVEY RESULTS
00

Company
Armco
Inland
Inland
Inland
LTVe
LTVe
LTVe
LTV
National


Plant
Middletown
Indiana Harbor
Indiana Harbor
Indiana Harbor
AHquippa
Aliquippa
Cleveland
Indiana Harbor
Granite City


Dust suppressants
used
Coherex® (200, 000 }c
Dustaside® (26,500)
Resinex 60® (29,500)
Flambinder (120,000)d
Petro Tac (6,000)c>f
Soil-Sement (18,000)c*f
Water and waste oil
Petro Tac (110,000)
Coherex®


Application
intensity h
(gal/yd^f
0.08/0.08
(20X/12X)
0.3/0.1
(17%/9%)
0.5/0.1
(17%/7 to 9%)
0.5/0.1
(181/10%)
N/A
N/A
N/A
0.5/0.5
(iox/iox)
0.28/0.28
/ 1 ~J*y / 1 T*y \
(I/A/IK)

Application Areas in which
frequency water is used
Once a week to Coal storage, recycle
every 6 months plant, slag process-
ing
Approximately
every 3 weeks
Approximately
twice per week
As needed, based
on visual in-
spection
N/A
N/A
N/A General dust mitiga-
tion
As needed, based
on visual ob-
servation
Once per week to
once per month
                                                      (continued)

-------
                                           TABLE 2-1 (continued)

Application
Dust suppressants intensity . Application
Company Plant used (gal/yd2) frequency
Areas in which
water is used
National Great Lakes Coherex® 0.09 Once per month
(15X)
USS
uss
USS
uss
Fairfield Dustaside® (6.000}9 N/A Quarterly during
the entire year
Gary Resinex 6(^ (500.000)9 N/A Daily rotation
through plant
Geneva Magnesium chloride N/A Every 6 months
Mono Valley Coherex® (50,000)a N/A N/A
Used as a supplement
on roads as needed
(usually once a day)
-
Open unpaved areas
on a weekly rotation
schedule
-

a
b
c
d
e
f
Value in parentheses is gallons delivered in 1984, except as noted.
Initial/follow-up applications. Value in parentheses represents dilution ratio.
1983 value.
Used primarily on storage piles and infrequently for light-duty roads
LTV data obtained during site surveys.
* * i






Estimated value.

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TABLE 2-2.   DUST  SUPPRESSANTS  RECENTLY USED OR CONSIDERED
              FOR EVALUATION
       Plant
  Middletown


  Indiana Harbor



  Aliquippa
  Indiana Harbor
  Corporate


  Gary

  Geneva
   Dust
suppressant
Comments
Resinex         Full scale program during
                1983

Generic         Corporate personnel have
                expressed interest, but
                have no plans to evaluate;

Dustaside®      Plant had hoped to purchase
                10,000 gal.  in 1984, but
                business conditions pre- i
                vented expenditure.  Dust-
                aside is preferred for
                1985                     i

Dustasidefi      Considering future evalua-
                tion

Soil Sement     Considering future evalua-
                tion

Coherex®        Evaluated in 1982

Resinex®        Evaluated in 1982

Generic         Corporate personnel have
                expressed interest

Dustaside®      Currently evaluating

Coherex®        Evaluated during 1982-1983;
                considered too expensive
                           10

-------
     On the basis of the above criteria,  no  site at the
suitable for  testing.   However,  one  suitable site was
Aliquippa and  Indiana  Harbor.   At the Aliquippa Works, the ^T
was approximately  1,600 ft long and  was  oriented southeast »s'
This road was used to haul both slag  to processing and refuse
                                                                       was
                                                                  3t both
                                                                ^^IQ  ~aad
                                                                -CT~hwest.
                                                                 = "lane-fill-
                                                              **£'
     The site at Indiana Harbor was the same  road that was
earlier study.1  However,  the BOF slag haul  road had  been  ;.J;
changed, with the southern half of the road isolated and dev»,t
hauling (approximately two round trips per hour).  This road
by the  slag  processor  at  the plant,  and Coherex® and calcium -
used to control emissions during 1384 and 1985,  respectively
part of the road carried a variety of vehicles,  ranging from -
ups to scrap trucks and Euclids.  This road was  maintained b/*
Tac has been applied since 1982.

                                                                      g an
                                                                r^ntially
                                                                : -.3 BOF slag
                                                                : maintained
                                                                " ;*"ide were
                                                                ~",e rsaaining
                                                                "i and pick-
                                                                "«, and Petro
site:
     In addition, the  dust  suppressants to be tested were at?-~a*
                                                                   to
     Aliquippa
     Indiana Harbor
                         CoherexS
                         Generic 2  (QS)
                         Soil Sement

                         Coherex®
                         Petro  Tac
                         Dustaside®
                                                               '.;• source of
                                                               .van.   Note
                                                               .-. Tiake inter-
In the  decision  process,  attention was paid to locating a n%a
the dust  suppressant and contractors  familiar with its app  -
that the petroleum resin  Coherex®  was  selected for both sittV
plant comparisons.

2.4  SELECTION OF STUDY DESIGN

     In developing  a study design to  characterize the cent?-.
of unpaved road dust  suppressants, both a sampling methodo 1 •„-•
application plan must be  chosen.   The  sampling method must >*
rately  characterize  the dust emissions,  and the  control ap-.,
must  be developed with attention  to possible  interference  s«
could impact control  efficiency  determination.

     Unpaved road  dust emissions  are  especially difficult  .-,
for the following reasons:

     1.   Both uncontrolled and  controlled emission rates h<,,%  -,
of temporal variability.

     2.   Emissions  are comprised  of a wide range of partic » --ze (includ-
ing coarse  particles which deposit  immediately adjacent to  -,-% source)  and
the control  efficiency for different  size ranges  can  vary
                                                               .^ a C0ntro1
                                                              >.'•'„ to accu-
                                                              IVlon plan
                                                                 -s which
                                    11

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The  scheme  for quantification of emission  factors  must effectively deal
with these  complications  to  yield source-specific emission data needed to
evaluate the priorities for  emission control  and  the  effectiveness  of  con-
trol measures.

     Two basic  techniques  have  been used in quantifying particulate emis-
sions from vehicular traffic on unpaved roads.

     1.    The upwind/downwjnd7 method involves measurement of concentrations
upwind and downwind of the source, utilizing ground-based samplers (usually
hi-vol samplers) under known meterological conditions.  Atmospheric disper-
sion  equations  are used to  back-calculate  the emission rate which most
nearly produces the measured concentrations.  The Gaussian dispersion equa-
tions art often applied to cases  of near-roadway  dispersion.  However,  the
equations generally  used  were  not  formulated  for  such an application.

     2.    MRI's exposure-profiling8 method  involves  direct measurement of
the total passage of open dust source emissions immediately downwind of the
source by  means of  simultaneous  multipoint sampling over the effective
cross-section of the open dust source emission  plume.   This technique  uses
a mass balance  calculation  scheme similar to EPA Method 5 rather than re-
quiring indirect calculation through the application of a generalized atmo-
spheric dispersion model.

     The most  suitable and accurate technique  for quantifying unpaved  road
emissions in the iron and steel  industry has been shown to be exposure pro-
filing.   The method  is source-specific  and  its  increased accuracy over the
upwind/downwind method is  a result of the fact that emission factor calcula-
tion is  based  on  direct  measurement of the variable sought, i.e., mass of
emissions per unit time.

     In addition to the above measurement techniques, the study design must
also include a control  application plan.  Two major types of plans have been
used:

     1.    Testing is conducted on two or more contiguous road segments.  One
segment  is  left untreated and the others are treated with a separate dust
suppressant.

     2.    Uncontrolled testing  is  initially performed on one or more road
segments, generally under worst-case (dry) conditions.  Each segment is then
treated with a different  chemical; there  is  no  segment  left untreated  as  a
reference.   A  normalization  of  emissions is required to allow for differ-
ences in vehicle characteristics during  the uncontrolled  and controlled
tests because they do not occur simultaneously.

     It  is  important to  note that, for  the  purpose of estimating annual
controlled  emissions from unpaved roads,  average  control efficiency values
based on worst-case  (i.e., dry)  uncontrolled emission levels  are  required.
                                   12

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This is true  simply  because the AP-42  unpaved  road  predictive  equation,6
which is routinely used for inventorying purposes, is based on source tests
conducted under dry  conditions.  Extrapolation  to  annual  average  emissions
estimates is  accomplished  by  assuming that emissions are occurring at the
estimated rate on days without measurable precipitation, and conversely are
absent on days with  measurable precipitation.  This  assumption has  never
been verified in a rigorous manner; however, MRI's experience with hundreds
of field tests  indicate  that  it is a reasonable assumption  if  the source
operates on a fairly "continuous" basis.

     The uncontrolled  emission  factor for a specific unpaved  road will  in-
crease substantially after a precipitation event as the surface dries.  How-
ever, in the  absence of data  sufficient to  describe  this  growth as a func-
tion of traffic parameters, amount of precipitation, time of day, season,
cloud cover, and other variables, uncontrolled emissions are estimated using
the simple assumption given above.   Thus, in order to definitively estimate
emission reductions  attributable to a dust  suppressant, control efficiency
should be referenced to uncontrolled emissions under dry conditions.

     The work plan for this study originally called for field testing to be
conducted over two summers.  However, because the study began in June 1984,
no testing was possible until the  spring of 1985.  Furthermore, it was  not
possible to  extend the project duration to include  the summer of 1986.
Because of the constraint of only one summer available for testing, the pro-
gram was designed  to obtain as  much useful  data as possible during the  pe-
riod.  In order to achieve this goal, modifications to MRI's prior dust con-
trol evaluation protocol  were  made.

     The first modification was the adoption of a Type 1 control application
plan.  The simultaneous  testing of both controlled and uncontrolled emis-
sions from the test  road under this plan allowed a more flexible set of ac-
ceptability criteria for  testing.   For  example, light rainfall during the
night did not require  that the  road dry out prior  to testing.   Thus,  adop-
tion of a Type 1 control  application plan allowed more tests to be completed.
However, control efficiency would  still be  referenced  to dry conditions.

     The second change (again  made possible by the Type 1 plan) also allowed
more information to  be collected during the field  program.  This  modifica-
tion entailed  deploying  an "abbreviated" sampling array on days that were
not totally acceptable for exposure profiling.  In this case, control effi-
ciency was determined on the basis of net reduction  in concentration values
rather than mass emission  rates.   In  addition to providing additional con-
trol performance data, this  information proved valuable (a) in evaluating
prior control effectiveness studies for  inclusion in model development, and
(b) in assessing the capability of simplified sampling protocols (i.e., not
requiring extensive  equipment or labor  resources) for  estimating control
efficiency.

     Thus, the study design for this testing program employed exposure pro-
filing as the primary  technique to quantity uncontrolled  particulate emis-
sions from vehicular traffic  on unpaved roads and  to determine  the control
                                   13

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performance of  the  various  suppressants.   This  design  not only ill owed the
evaluation  of  effectiveness for each suppressant  but  could also provide
information on  the  seasonal  variation of  uncontrolled  emissions.  Finally,
the inclusion of a secondary sampling array had the additional benefits de-
scribed above.

     The rest  of this  section  describes the detailed test methodology, in-
cluding air and surface material sampling equipment and techniques, field
and laboratory analysis techniques, and calculation procedures.

2.5  QUALITY ASSURANCE

     As part of the QC program for this study, routine audits of sampling
and analysis procedures  were performed.   The purpose of the audits was to
demonstrate that measurements were made within acceptable control conditions
for particulate source sampling and to assess the source testing data for
precision and accuracy.  Examples of items audited include gravimetric anal-
ysis, flow  rate calibration, data processing, and  emission factor and  con-
trol efficiency calculation.   Specially designed reporting forms for field
sampling and laboratory analysis data aided in the auditing procedure.   Fur-
ther detail on specific sampling and analysis procedures are provided  in the
following sections.

2.6  AIR SAMPLING EQUIPMENT AND TECHNIQUE

     Exposure profiling, which was  the  primary air sampling  technique in
this study, is  based on the isokinetic profiling  concept used in conven-
tional source testing.   The passage of airborne pollutant immediately down-
wind of the source was measured directly by means of simultaneous multipoint
sampling over  the effective cross section of the  open  dust source  plume.
This technique used a mass-balance calculation scheme similar to EPA Method 5
stack testing rather than requiring indirect calculation through the appli-
cation of a generalized atmospheric dispersion model.

     In addition, an abbreviated sampling array was deployed when conditions
at the site were not fully suitable for exposure profiling.  This secondary
system was  designed to provide particulate concentration  data (rather  than
mass emissions  data)  for calculation of control efficiency.   Use of this
system during periods of marginal wind conditions was designed to provide as
much control efficiency data as possible in the 1 year available to MRI for
testing.  The air samplers that were used in the field testing are  listed  in
Table 2-3.   The two sampling arrays are discussed separately below.
                                   14

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                     TABLE 2-3.   AIR SAMPLING EQUIPMENT
                                               Intake height (m)
   Location         Sampler            Full array      Abbreviated array


   Upwind3       Standard hi-vol/          2.2                2.2
                   impactor
Downwi nd
station




Profiling head



Cyclone/impactor
37-mm cassette
1.5
3.0
4.5
6.0
2.2
2.2
-
-
-
-
2.2
2.2

      This deployment was modified for testing at Indiana Harbor because
      of the potential difference in upwind concentrations.   Standard
      hi-vol/impactor combinations (each at a 2.2-m height}  may be
      located upwind of each test strip.


     The MRI exposure profiler (developed under EPA Contract No. 68-02-0619)
was used in the "full" array.   Each profiler (Figure 2-4) consist of a por-
table tower (4 to 6 m height)  supporting an array of sampling heads.  During
testing, each  sampling head was  operated as an  isokinetic exposure  sampler
directing passage of  the flow stream through a  settling chamber and then
upward  through a standard 20.3-  x 25,4-cm  (8- x  10-in.) glass fiber filter
positioned horizontally.   Sampling  intakes were  pointed  into the wind, and
sampling velocity of  each intake was adjusted to match the  local mean wind
speed, as determined by 5- to  10-min averages prior to and during the test.

     High-volume, parallel-slot cascade impactors (Sierra Instruments,  Model
No. 230) with  34-m3/hr  (20-cfm)  flow controllers were used to measure the
downwind particle size distribution along  side  the  exposure profiler.  The
height  selected  for  the  downwind samplers was  based  on an  examination of
previous MRI testing.1 3  This height reasonably approximates the point  in
the dust plume at  which  half the mass emissions are above and half below.

     The downwind impactor units (as shown in Figure 2-5) were equipped with
Sierra  Model No.  230CP  cyclone  preseparators to  remove  coarse  particles
which otherwise  would tend  to bound off  the  glass fiber impaction sub-
strates, causing fine particle measurement bias.  To further reduce particle
bounce problems,  each substrate was sprayed with stopcock grease solution to
provide a  sticky impaction  surface.  The upwind particle size distribution
was measured using hi-vol/impactor combinations.  Experience has shown that
the background size  distribution is essential in determining control effi-
ciencies for fine  particulate emissions.   Each impactor consisted of five


                                   15

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Figure 2-4.   MRI exposure profiler.
                 16

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      Seal*'- Inewt
                                                S STAGE CASCAOf
                                                IM? ACTOR
                                                      BACK-UP MLTSJt
                                                      htCLOER
Figure  2-5.   Cyclone preseparator/ciscade impactor combination.


                                   17

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impaction stages  (cut-offs  for 50% collection  are  10.2,  4.2,  2.1,  1.4,  and
0.73 umA at 20 ACFM).   In order to determine the particle size distributions
at the  coarse  particle  end of the spectrum  by microscopy,  37-mm cassette
samplers were  deployed  at  the same  locations as  the  cyclone/impactors.

     Throughout each test, wind speed was monitored by warm-wire anemometers
(Kurz Model 465)  at two heights, and  the  vertical wind  speed profile was
determined by  assuming  a  logarithmic distribution.  An integrating Biram's
vane anemometer was used as a backup system.   Horizontal  wind direction was
monitored by a wind vane at a single height,  and 5- to 10-min averages were
determined electronically prior  to  and during the test.   The sampling in-
takes were adjusted for proper directional  orientation based on the average
wind direction.

2.7  EMISSION TESTING PROCEDURE

2.7.1  Preparation of Sampl_e_Co_l 1 ection Media

     Particulate samples were  collected on Type A slotted glass fiber im-
pactor substrates and on Type AE  grade glass  fiber filters.   As noted in the
last section,  all  glass fiber cascade impactor substrates were greased to
reduce the problem of particle bounce.   The grease solution was prepared by
dissolving 140 g  (4.9 oz)  of stopcock grease in 1 L (0.26 gal) of reagent
grade toluene.  No  grease was applied  to the borders and backs of  the sub-
strates.  The  substrates  were  handled, transported, and  stored in frames
which protected the greased surfaces.

     Prior to the initial  weighing,  the filters and greased substrates were
equilibrated for  24 hr  at constant  temperature and humidity  in a  special
weighing room.   During weighing,  the balance  was checked at frequent inter-
vals with standard  (Class  S) weights  to assure accuracy.  The filters and
substrates remained in  the  same  controlled environment for another 24 hr,
after which a second analyst reweighed them as a precision check.   If a sub-
strate or filter could not pass audit limits, the entire lot was reweighed.
Ten percent of the substrates  and filters  taken to the field were used as
blanks.   The quality assurance guidelines pertaining to preparation of sam-
ple collection media are presented in Table 2-4.

2.7.2  Pretest Procedures/Evaluation of Sampling Conditions

     Prior to  equipment deployment,  a number of decisions were made as to
the potential  for  acceptable source  testing  conditions.   These decisions
were based on  forecast  information  obtained from  the  local  U.S.  Weather
Service office.   Sampling  was  not planned if there was a high probability
of measurable precipitation.

     If conditions  were considered  acceptable, the sampling equipment was
transported to the site, and deployment was initiated.   The deployment pro-
cedure normally took 1 to 2 hr to complete.  During this time, the sampling
flow rates were  set for the various air sampling  instruments.  The quality
control  guidelines governing this activity are found in Table 2-5.
                                   18

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        TABLE 2-4.   QUALITY ASSURANCE PROCEDURES FOR SAMPLING MEDIA
      Activity
     QA check/requirement
Preparation


Conditioning
Weighing
Auditing of weights
Correction for handling
  effects
Calibration of balance
Inspect and imprint glass fiber media with
identification numbers.

Equilibrate media for 24 hr in clean con-
trolled room with relative humidity of less
than 50% (variation of less than ± 5%) and
with temperature between 20°C and 25°C
(variation of less than ± 3%).

Weigh hi-vol filters and impactor substrates
to nearest 0.1 mg.

Independently verify final weights of 10% of
hi-vol filters and impactor substrates (at
least four from each batch).   Reweigh batch
if weights of any hi-vol filters or impactor
substrates devote by more than ± 2.0 mg and
± 1.0 mg, respectively.   For tare weights,
conduct a 100% audit. Reweigh tare weight of
any Imvol filters or impactor substrates
that deviate by more than ± 1.0 mg, and
± 0.5 mg, respectively.

Weigh and handle at least one blank for each
1 to 10 hi-vol filters or impactor sub-
strates of each type for each test.

Balance to be calibrated once per year by
certified manufacturer's representative.
Check prior to each use with laboratory
Class S weights.
                                     19

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     TABLE 2-5,   QUALITY ASSURANCE PROCEDURES FOR SAMPLING FLOW RATES
        Activity                            QA check/requirement


Calibration
  *  Cyclone/impactors            Calibrate flows in operating ranges using
                                  calibration orifice upon arrival and
                                  every 2 weeks thereafter at each plant
                                  prior to testing.

  •  Profiler heads               Calibrate flows in operating ranges
                                  using calibration orifice upon arrival
                                  and every 2 weeks thereafter at each
                                  regional site prior to testing.

  •  Orifice and electronic       Calibrate against displaced volume test
       calibrator                 meter annually.
     Once the source testing equipment was set up and the filters inserted,
air sampling commenced.   Information was recorded on specially designed re-
porting forms for quality assurance and included;                     i

     a.   Exposure profiler -  Start/stop  times,  wind speed profiles, and
          sampler flow  rates  (5- to 10-min average), and wind direction
          relative to  the roadway perpendicular  (5-  to 10-min average),

     b.   Other samplers - Start/stop times and flow rates,           •

     c.   Traffic count by vehicle type and speed,

     d.   General meteorology - Wind speed, wind direction, and temperature.

     From the  information  in (a),  adjustments  could be  made to  insure iso-
kinetic sampling of both profiler heads (by changing the intake velocity and
orientation) and cyclone preseparators (by changing intake nozzles and ori-
entation).  Table 2-6 outlines the pertinent QA procedures.

     Sampling time was  long enough to provide sufficient particulate mass
and to  average  over  several cycles of  the  fluctuation in  the  emission rate
(i.e.,  vehicle  passes  on the road).    Sampling lasted from 16 min to over
4 hr depending  on source activity  and  control  measure (if any).   Occasion-
ally,  sampling  was  interrupted due to occurrence of unacceptable meteoro-
logical conditions and  then restarted when suitable  conditions returned.
Table 2-7 presents the criteria used for suspending or terminating a source
test.                                                                :
                                   20

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      TABLE 2-6.   QUALITY ASSURANCE PROCEDURES FOR SAMPLING EQUIPMENT
        Activity
          QA check/requirement3
Maintenance
  *  All samplers
Operation
  •  Timing
     Isokinetic sampling
       (profilers only)
     Isokinetic sampling
       (cyclone/impactors)
     Prevention of static
       mode deposition
Check motors, gaskets, timers, and flow
measuring devices at each plant prior
to testing.
Start and stop all samplers during time
span not exceeding 1 min.

Adjust sampling intake orientation when-
ever mean wind direction changes by more
than 30 degrees.

Adjust intake velocity whenever mean
wind speed approaching sampler changes
by more than 20%.

Adjust sampling intake orientation when-
ever adjustments are made to the exposure
profiler intake orientation.

Change the cyclone intake nozzle whenever
the mean wind speed approaching the sam-
pler falls outside of the suggested
bounds for that nozzle.   This technique
allocates no nozzle for wind speeds rang-
ing from 0-6 mph,  and unique nozzles for
each of the wind speed ranges 6-8, 8-11,
11-15, and 15-20 mph.

Cap sampler inlets prior to and immedi-
ately after sampling.
   All means refer to 5- to 10-min averages.
                                     21

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       TABLE 2-7.   CRITERIA FOR SUSPENDING OR TERMINATING AN EXPOSURE
                     PROFILING TEST
A test may be suspended or terminated if:a

1,   Rainfall ensues during equipment setup or when sampling is in progress.

2.   Mean wind speed during sampling moves outside the 1.3- to 8.9-m/sec (3-
    to 20-rnpn) acceptable range for more than 20% of the sampling time.

3.   The angle between mean wind direction and the perpendicular to the path
    of the moving point source during sampling exceeds 45 degrees for two
    consecutive averaging periods.                                     '.

4,   Daylight is insufficient for safe equipment operation,

5.   Source condition deviates from predetermined criteria (e.g., occurrence
    of truck spill, or accidental water splashing prior to uncontrolled
    testing).


a  "Mean" denotes a 5- to 10-min average.


2.7,3  SampleHandling and Analysis

     To prevent particulate losses, the exposed media were carefully trans-
ferred at the end  of  each  run to protective  containers  for transportation.
In the field laboratory, exposed filters were placed in individual glassine
envelopes and then into numbered file folders.   Impactor substrates were
replaced in  the  protective frames.   Particulate that collected on the in-
terior surfaces  of profiler intakes and cyclone  preseparators was rinsed
with distilled water  into  separate sample jars which were then capped and
taped shut.

     When exposed  substrates  and filters (and the associated blanks) were
returned to  the  MRI  laboratory,  they were equilibrated  under  the  same  con-
ditions  as  the  initial  weighing.   After reweighing,  10%  were audited to
check weighing accuracy.

     To determine the sample weight of particulate collected on the interior
surfaces of  samplers,  the  entire wash solution was passed through a 47-mm
(1.8-in.) Buchner-type  funnel  holding a glass fiber filter under suction.
This water was passed through the Buchner funnel ensuring collection of all
suspended material  on the  47-mm filter which was then dried  in an oven at
100°C for 24 hr.   After drying, the filters  were conditioned at  constant
temperature and humidity for 24 hr.
                                   22

-------
     All wash filters  were  weighed with a  100%  audit  of tared and a
audit of exposed  filters.   Blank values were determined  by washing  "clean"
(unexposed) profiler intakes in the field and following the above procedures.

2.7.4  EmissionFactor Calculation Procedure                                :

     To calculate emission  rates using the  exposure profiling technique, a
conservation of mass approach is used.  The passage of airborne particulate
(i.e., the quantity  of emissions  per unit of source activity) is obtained  :
by spatial integration of distributed measurements of exposure (mass/area)
over the effective cross section of the plume.   Exposure is the point value
of the  flux  (mass/area-time)  of airborne particulate integrated over the
time  of  measurement,  or equivalently, the  net particulate mass passing    :
through a unit area normal  to the mean wind direction during the test.   The ;
steps in the calculation procedure are described below.

Particulate Concentrations—                                                ;
     The concentration of particulate matter measured by a sampler is given
by:                                                                         i


                              C = 10* J
where;     C = particulate concentration (ug/m3)
          m = particulate sample weight (mg)
          Q = sampler flow rate (nrVmin)
          t = duration of sampling (min)

     The specific particulate matter concentrations were determined from the
various particulate catches as follows:

        Size range                    Particulate catches

           TP              Profiler filter + intake or
                             cyclone + impactor substrates + backup filter

           IP              Impactor substrates + backup filter

           PM10            Impactor substrates * backup filter

           FP              Impactor substrates +• backup filter


To be  consistent  with the National Ambient Air Quality Standard for total
suspended  particulate (TSP),  all  concentrations and  flow  rates  were ex-
pressed in standard conditions (25°C and 101 kPa or 77°F and 29.92 in. Hg).
                                   23

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Isokinetic Flow Ratio—
     The isokinetic flow ratio (IFR) is the ratio of a directional  sampler's
intake air speed  to  the mean wind  speed  approaching  the sampler.   It is
given by:
where:    Q = sampler flow rate (mVmin)
          a = intake area of sampler (ra2)
          U = mean wind speed at height of sampler (m/rain)


This  ratio  is of  interest in the sampling of TP, since isokinetic sampling
assures that particles of all sizes are sampled without bias.   In this study,
profilers and  cyclone preseparators were the  directional  samplers  used.

     Occasionally it  is necessary to sample at a superisokinetic flow rate
(IFR > 1.0), to obtain sufficient sample under light wind conditions.   Cor-
rection factors for nonisokinetic TP concentrations are based  on a relation-
ship developed by Davies.9  The relationship as applied to exposure profil-
ing in the ambient atmosphere is as follows:


                         5l - JL-   d/IFR)  "I
                         Ct ~ IFR "   4Y + 1


where:  C  = nonisokinetic concentration of  particles of diameter d

        (L - true concentration of particles of diameter d            ;
         t                                                            ;
         Y = inertia! impaction parameter =  d2 c (p  - p) U/18u D

         D - diameter of probe

         d = diameter of particle
         p = density of air                                           I

         u - viscosity of air

        p  = density of particle

         c = Cunningham correction factor                            I


From  Oavies1 equation,  it is clear that, for  very small d,  C  = Cfc,  and
that, for large  values  of d, C  = Ct/IFR.  These observations lead to_the
multiplicative correction  factors presented  in  earlier MRI  reports.2 4
                                   24

-------
     A value for the average  ratio  (R)  of  nonisokinetic to true
can be found by integrating the product of the particle size di
Davies1 relationship over all possible  particle diameters.  An
corrected concentration can then be calculated as
                                                                          and
                                                                ~nt-  f
                                                                tOKirmi
                                       Cfl/R
     Note that,  because the particle-size  distribution and  the  i  i,-  t'c
corrections are  interrelated,  isokinetic corrections  are of an  .s   ".
nature.   In  the present  study,  isokinetic corrections based  on n*-   '
method described above were iterated  until  a convergence -criterj     -  1%.
difference between successive TP concentration values  was jati-f-°T  OT
                                                           •»« <• i ,» j I OQB

     Using a  log-normal distribution of particlj diameter^  tne  .  . .
cally corrected  concentrations obtained by  the R-method and  by MfqS|°
multiplicative correction  factor method differ  by less tnan 20% f
values between 0,2 and  1.5, by less  than 30%  in the IFR ranqt  of i TV
and by less than 601 for IFR values  between 2.0 and 3.Q.1         b to
                                                                          n
                                                                           '
Downwind Particle-Size Distributions —
     Particle-size  distributions  were determined by plotting ran     f th
cumulative concentrations measured  by each impactor stage to  *h<* * h°s  °
                                                              "  " rL°   ri ft
                                                              ^ar, . se da'ca
                                                               *--1on  for
centration against  the 50% cutoff diameters presented ear
were  fitted  to a lognormal  mass size distribution  after -
particle bounce,                                           "
     The technique used  in this  study to correct for the s-**a.-t-  f    +- -,
bounce has been discussed in  earlier  MRI studies.1'2'3  3 -su^n,,,  Partic'e
impactor measurements of airborne  particle-size d1stribur-,n •liirf,''
out a  cyclone  precollector  indicate that the cyclone prec'/iecv,!- -
effective  in reducing fine particle  measurement bias,   Hf^»./(j"r''   1S
the cyclone precollector, a monotonic decrease in collect!;':
on each successive impaction  stage is frequently followed v
increase in weight collected  on  the back-up filter.   But, -,
value  (0.2 M"i)  for the effective cutoff diameter of the  9
filter fits  the progression  of  cutoff diameters for the
the weight collected  on  the back-up filter should be cons
creasing pattern shown by the weight  collected on the imq.
excess particulate on the back-up  filter is postulated tc
particles  that  penetrated the cyclone (with small probab
through the impactor.  Although  particle bounce is furth
ing impaction substrates, it  is  not completely eliminates
discussion of  techniques used to  reduce the effects of p
given  elsewhere.1
                                                           -,'»'- ag^^         H
                                                           «V*:. 0  h as,sum
                                                           -icac.--/"r      p
                                                           -,*.er,iT*
                                                           '.*^'-^,,    2   h
                                                           '.-.n^-;^"3?5"      e
                                                           :»y^  V ^j t> C° red
                                                            -or;yrs.(| °ou _eas_
                                                             A ?ir]
-------
     1.  The calibrated cutoff diameter for the cyclone preseparator is used
to fix the upper end of the particle-size distribution.

     2.  The lower  end of the particle size distribution  is  fixed  by  the
cutoff diameter of the last stage and the measured (or correcteds if neces-
sary) mass fraction collected on the back-up filter.   The corrected fraction
collected on the  back-up  filter is calculated as the average of the fric-
tions measured on the last two stages (Stages 4 and 5).

     When a corrected  mass  is required, excess particulate mass is effec-
tively removed from the back-up filter.   However, because no clear procedure
existed for apportioning the excess mass back onto ttie impaction stages, the
size distribution determined for tests with evidence of particle bounce was
constructed using the  log-normal assumption and  two points—the mass frac-
tion collected  in the  cyclone and  the corrected  mass fraction collected on
the back-up filter.   The mass fractions associated with the first few impac-
tion stages usually lie very near this line.

     Prior examination of particle bounce corrections has shown only negli-
gible changes in  size  fractions for  PM10 and above.  Furthermore, FP frac-
tions generally are within  a factor of 1.2 when compared to fractions de-
veloped without any correction for particle bounce.10

Particulate Exposures and Profile Integration—
     For directional  samplers  operated isokinetically, total particulate
exposures are calculated by:


                         E = 10"7 x CUt


where:     E ~ total  particulate exposure (mg/cm2)                      !
          C = net TP concentration (ug/m3)                             i
          U = approaching wind speed (m/s)                             ,
          t ~ duration of sampling (s)                                 i


     The exposure values vary over the height of the plume.  If exposure is
integrated over the height  of the  plume, then  the quantity obtained repre-
sents the  total passage of airborne particulate matter due to the  source
per unit length of the line source.  This quantity is called the integrated
exposure A and is found by:


                              H
                         A = J*   E dh
                            0                                          ;


where:     A = integrated exposure  (m-mg/cm2)
          E - particulate exposure (mg/cm2)
          h = vertical distance coordinate (m)
          H = effective extent of plume above ground (m)

                                   26                                  !

-------
The effective  height  of the plume is found by linear extrapolation of the
uppermost net TP concentrations to a value of zero.

     Because exposures are measured at discrete heights of the plume, a nu-
merical integration is  necessary to determine A.  The exposure must equal
zero at the vertical extremes of the profile (i.e., at the ground where the
wind velocity equals zero and at the effective height of the plume where the
net concentration equals  zero).   However, the maximum TP exposure usually
occurs below a height of 1 m, so that there is a sharp decay in TP exposure
near the ground.  To account for this sharp decay, the value of exposure at
the ground level is set equal to the value at a height of 1 m.  The integra-
tion is then performed using Simpson's rule.

Total Particulate Emission Factoi—
     The emission factor for total airborne particulate generated by vehicu-
lar traffic on  a straight road  segment  expressed  in  grams  of  emissions per
vehicle-kilometer-traveled (VKT) is given by:


                         e = 10*
where:    e = total particulate emission factor (g/VKT)
          A » integrated exposure (m-mg/cm2)
          N = number of good vehicle passes (dimensionless)


Other Emission Factors--
     Emission factors  for  the other particle size ranges were obtained by
multiplying the  emission  factors  by net mass fractions.  These mass frac-
tions are  found  by dividing the net (i.e., downwind minus upwind) concen-
tration for the size range of interest by the net TP concentration.

2-7.5  Control Ef.ficiency_CaT_cu1ati onProcedure

     Although controlled  and  uncontrolled  tests were  conducted at the  same
site, it was  necessary to obtain normalized values of emission factors in
order to make meaningful comparisons.  This was true simply because the ve-
hicle mix  on  the test  road varied  not  only from day to  day  but also  during
different  shifts  on an individual  day.   Thus,  measurement-based  ("raw")
emission factors  required  normalization in order that a change in vehicle
mix was not mistakenly interpreted as part of the efficiency of the control
measure being tested.

     The method  used in this study to normalize emission factors  is based
on MRI's experimentally determined predictive  emission  factor equation for
uncontrolled  unpaved roads and  is  identical  to  the process  used in earlier
reports.1'2  The emission  factors are scaled by:
                                    27

-------
where;    e  = normalized value of the emission factor corresponding to
               run i                                             *

          e. = measured emission factor from run i

          S  = normalizing value for average vehicle speed

          S. * average vehicle speed during run i
                                                                      !
          W  = normalizing value for average vehicle weight

          W. = average vehicle weight during run i                    j

          w  = normalizing value for average number of wheels per vehicle
               pass                                                   i

          w, = average number of wheels per vehicle pass during run i



The control efficiency in percent (c) is then found as:
                            c = fI - -£ 1 x 100%

                                     S

where:    e  = normalized emission factor for controlled road

          e  = geometric mean of normalized emission factors for
               uncontrolled roads


This  value of  efficiency represents the (instantaneous) level of control
over  a specific test (and, hence, at a  particular time after application).

     Another important measure of control performance is average efficiency
defined as:
                         C(T) = |   /   c(t) dt
                                  o
                                   28

-------
where:  C(T) = average control efficiency  during  period ending T days  after
               application (percent)

        c(t) = instantaneous control efficiency at  t  days  after application
               (percent)

           T = time period over which  average  control  efficiency is  desired
               (days)


This  value  enables  one to determine mass  reductions in emissions for thi»
purpose of determining cost-effectiveness,

2.8  AGGREGATE MATERIAL SAMPLING AND ANALYSIS

     Samples of  the loose road surface  were taken from lateral strips or
known area (generally, the width of the  road by 30  cm)  during the course  <>f
this  study.  These  were analyzed  for  silt (those particles passing  a  200-
mesh  screen) and moisture contents and  to determine road surface loading
values.  Detailed steps for collection and analysis of samples for silt ,ind
moisture are given  in a previous report,8   An  abbreviated  discussion is pre-
sented below.

     Roadway surface dust samples  were collected  by sweeping the loose l.i/op
of  soil,  slag,  or crushed rock from the hardpan road base with a broom a(,rj~
dust  pan.   Sweeping was  performed so that the road base was not abraded by
the broom, and so that only the naturally  occurring loose  dust was colleu,ecj
The sweeping was performed slowly so  that dust was not entrained into tlni"
atmosphere.

     Once the field sample was obtained,  it was prepared for analysis,   [i)(3
field  sample was split (if necessary) with a  riffle to a  sample size      "
nable to laboratory analysis.  The basic procedure  for moisture analysis
determination of weight loss  upon oven drying.  Table  2-8 presents a st%-
by-step procedure for determining  moisture content.  The basic procedure  ;or
silt  analysis  was  mechanical, dry sieving.  A step-by-step procedure i-.
given  in Table 2-9.

2.9   AUXILIARY EQUIPMENT  AND  SAMPLES

      Provision was  made to quantify additional parameters which affect t,-,«.
performance of a control  measure applied to unpaved roads.  These parameters
include:

      1.  Intensity  of  the control  application;

      2.  Number  of  vehicle  passes  following application;

      3.  Vehicle mix of  traffic  on the controlled road; and

      4.  Vehicle speed measured  by a hand-held radar gun.
                                    29

-------
                 TABLE 2-8.   MOISTURE ANALYSIS PROCEDURES
1.   Preheat the oven to approximately 110°C (230°F).  Record oven tempera-
     ture.                                                             |

2.   Tare the laboratory sample containers which win be placed in the ;
     oven.  Tare the containers with the lids on if they have lids.  Record
     the tare weight(s).  Check zero before weighing.

3.   Record the make, capacity, smallest division, and accuracy of the
     scale.

4.   Weigh the laboratory sample in the container(s).  Record the combined
     weight(s).  Check zero before weighing.

5.   Place sample in oven and dry overnight.3                          j

6.   Remove sample container from oven and (a) weigh immediately if uncov-
     ered, being careful of the hot container; or (b) place tight-fitting
     lid on the container and let cool before weighing.  Record the com-
     bined sample and container weight(s).  Check zero before weighing.

7.   Calculate the moisture as the initial weight of the sample and con-
     tainer minus the oven-dried weight of the sample and container divided
     by the initial weight of the sample alone.  Record the value.

8.   Calculate the sample weight to be used in the silt analysis as the
     oven-dried weight of the sample and container minus the weight of the
     container.  Record the value.
   Dry materials composed of hydrated minerals or organic materials like
   coal and certain soils for only 1-1/2 hr.  Because of this short dry-
   ing time, material dried for only 1-1/2 hr must not be more than
   2.5 on (1 in.) deep in the container.
                                     30

-------
                   TABLE 2-9.   SILT ANALYSIS PROCEDURES
 1.   Select the appropriate 8-in.  diameter,  2-in,  deep sieve sizes.   Recom-
     mended U.S.  Standard Series sizes are:   3/8 in.,  No.  4, No.  20,
     No.  40, No.  100,  No.  140,  No.  200, and a pan.   Comparable Tyler Series
     sizes can also be utilized.   The No.  20 and the No.  200 are mandatory.
     The others can be varied if the recommended sieves are not available
     or if buildup on  one particular sieve during sieving indicates that an
     intermediate sieve should be inserted.

 2.   Obtain a mechanical  sieving device such as a vibratory shaker or a
     Roto-Tap (without the tapping function).

 3.   Clean the sieves  with compressed air and/or a soft brush.  Material
     lodged in the sieve openings or adhering to the sides of the sieve
     should be removed (if possible) without handling the screen roughly.

 4.   Obtain a scale (capacity of at least 1,600 g) and record make, capac-
     ity, smallest division, date of last calibration, and accuracy.

 5.   Tare sieves and pan.   Check the zero before every weighing.   Record
     weights.

 6.   After nesting the sieves in decreasing order with the pan at the bot-
     tom, dump dried laboratory sample (probably immediately after moisture
     analysis) into the top sieve.   The sample should weigh between 800 and
     1,600 g (1.8 and  3.5 Ib),    Brush fine material adhering to the sides
     of the container  into the top sieve and cover the top sieve with a
     special lid normally purchased with the pan.

 7.   Place nested sieves into the mechanical device and sieve for 10 min.
     Remove pan containing minus No. 200 and weigh.  Repeat the sieving
     in IQ-min intervals until  the difference between two successive pan
     sample weighings  (where the tare of the pan has been subtracted) is
     less than 3.0%.  Do not sieve longer than 40 min.

 8.   Weigh each sieve  and its contents and record the weight.  Check the
     zero before every weighing.

 9.   Collect the laboratory sample and place the sample in a separate con-
     tainer if further analysis is expected.

10.   Calculate the percent of mass less than the 200-mesh screen (75 urn).
     This is the silt content.


   This amount will vary for finer textured materials; 100 to 300 g may
   be sufficient when 90% of the sample passes a No. 8 (2.36-mm) sieve.
                                     31

-------
Because the efficiency  associated with a control measure is only directly
applicable to a particular dilution  ratio  and  application  intensity,  it is
important that these variables be quantified.

     By either working closely with plant personnel or actually contracting
the work, MRI was able to directly oversee the mixing and application of the
solution.  To measure the  application intensity, tared sampling pans were
placed at various locations on the road surface prior to application.  These
pans were detp enough  (- 15 cm) that material splashing on the bottom did
not escape.

     After the control was applied,  the sample pans were reweighed  and  the
density of the solution  determined.   The application  intensity measured by
each pan is given by:
                                       ~ m..
                                      P A
where:    a = application intensity (volume/area)

         m,- = final weight of the pan and solution (mass)

         nL ~ tare weight of the pan (mass)

          p = weight density of solution (mass/volume)

          A = area of the pan (area)


Application intensities measured by each pan were examined  for  any  spatial
variation.

     In order to define decay as a function of traffic rate as well as time,
pneumatic tube axle counters were deployed at the site after control appli-
cation.   In addition  to  vehicle counts during testing, independent counts
determining the distribution of vehicles by number of axles were taken dur-
ing each  shift  at the plant.  This information  was  used to convert axle
counts into the number of vehicle passes.
                                   32

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                                SECTION 3.0

                  CHRONOLOGY OF THE FIELD TESTING PROGRAM
                             AND TEST RESULTS
     The preceding  section described  the  study  design  and  testing  plan  for
this field program; however,  several unanticipated events necessitated that
portions of the original plans be altered.  This section discusses the pro-
gram as it evolved in response to these events.   In addition, field results
are presented and discussed.

3.1  MODIFICATIONS TO TEST PLAN

     MRI field testing  personnel  arrived at LTV's Indiana Harbor Works on
Monday, April 29,  1985.   During  the next few days,  several  conversations
between MRI and Preventive Maintenance Corportion (PMC) representatives took
place at the plant.  (At  the  time,  the  Indiana  Harbor  Works  was  separately
evaluating PMC s Dustaside® at various locations In the plant.)  After sev-
eral telephone calls by both  parties  to the project  officer,  PMC requested
that Dustaside® not be included in the field evaluation.

     Further discussions  with the plant's environmental  staff revealed  in-
terest in the calcium chloride dust suppressant (Liquidow®) used by the BOF
slag processor.  Much of this interest was due to the  low cost and the fact
that the supplier  applied the material, thus eliminating certain costs in
common dust control plans.  Arrangements  were made to  obtain calcium  chlo-
ride as the third chemical for evaluation at Indiana Harbor.

     On May 17, 1985, with MRI personnel present at Indiana Harbor, LTV an-
nounced that the  Aliquippa Works would be closed.   Subsequent discussion
with personnel  at both plants revealed that, although  August  17 would be the
target date  for cessation of  many  operations,  steel making would  end on
June 28.   Thus, only  negligible  traffic would be present on  the slag haul
road at Aliquippa after June 1981.

     In a meeting  with  the EPA technical  monitor  in  Kansas City  on May  23,
several options were  discussed in order  to continue the field efforts  in
the most productive manner possible.   Both MRI and  the technical  monitor
agreed that testing at  the Kansas City  Works of Armco, Inc.,  would be pre-
ferred for the following reasons:

     1.   Little time would be lost in conducting a new site  survey because
          this road had been  used in an earlier study1
                                  33

-------
     2.   Travel costs would be reduced

     3.   The road at Armco was  long enough  to  permit  five  contiguous  test
          sections so that all five chemicals could be evaluated on the same
          road

     4.   MRI would be  able  largely to control the service environment of
          the road in order to simulate typical industry traffic character-
          istics

     Drums of Cohere)®  and Generic which  had earlier been delivered  to the
Aliquippa Works were shipped to Kansas City.   Furthermore, arrangements were
made to  obtain  Petro Tac and  Soil Sement  in  small  lots and  to  have calcium
chloride available for application in Kansas City.

3.2  SOURCE DESCRIPTION

     The following tests were performed at two iron and steel plants - LTV's
Indiana Harbor  Works (designated hereafter as plant AP) and Armco's  Kansas
City Works (plant AQ):
Plant AP
          Five tests of uncontrolled emissions
          Six tests on a road treated with Cohere*®
          Six tests on a road treated with Petro Tac
          Three tests on  a  road treated with calcium chloride (Liquidow®)
Plant AQ
          Two tests of uncontrolled emissions
          Nine tests on a road treated with Coherex®                  ;
          Eleven tests on a road treated with Soil Sement
          Eleven tests on a road treated with Generic 2 (QS)
          Five tests on a road treated with Petro Tac                 ;
          Six tests on a road treated with Liquidow©
         T^i
     Maps of the  test sites at plants AP  and AQ  are shown  as  Figures; 3-1
and 3-2, respectively.   Areas  shown as buffers at  the AP test site were
treated with either calcium chloride or Petro Tac;  in addition, open  areas
in the  scrap storage  yard south of  the road were  treated  with  Petro Tac  to
reduce potential upwind impacts.

     Several difficulties in controlling  traffic patterns  at  the  AP  site
were encountered.   For example, scrap steel and processed slag haulers often
entered the test area at the southwest corner of the pipe mill, traveled be-
tween the slag  piles  and the mill  and made  U- turns onto the scale.   The
plant erected a barricade using barrels and plastic  streamers at the mill's
southwest corner;  this, however,  did not prove effective.   Later, barricades
made by piling slag proved to be much more effective.
                                  34

-------
UJ
en
           too
        \±
       o
                      N
                      I
                           SEAMLESS  PIPE  MILL.
                                       /n*t fdanr canr/To/ {Rtrro
300
500
                     400
                   i	I
                                        —j CattTGOtLED TEST

                                                       Cti/oric/e
                        JSOm
                           Figure 3-1.  Test site at plant AP,

-------
N
      150m
          Figure 3-2.  Test site at plant AQ.

-------
     The AQ  test  site, on  the  other hand,  allowed MRI  much greater control
of the service environment for the test sections.  This road was located in
a remote corner of the plant and  experienced only sporadic traffic related
to plant security and maintenance of a levee to the southeast.  Arrangements
were made with the plant's slag processor  to fill  and  grade turnarounds  at
the east and west ends  of the road to accomodate captive  traffic  supplied
by MRI.  The captive  traffic consisted of  a  10-ton,  6-wheel dump truck pe-
riodically supplemented with an R-25 Euclid.   All travel was confined  to the
north side of the road;  this not only accelerated the decay rate under traf-
fic but also decreased the road length required for a test  section.

     The AQ test road experienced average traffic volumes  of 110 and 130 ve-
hicle passes  (VP) per working  day between  September  3  and  October  3, 1985,
and between October 21 and the end of testing, respectively.  Because  vehi-
cles were restricted to one side of the road, these volumes represent  220 to
260 passes per day for  two-way traffic.   These two-way equivalent volumes
closely approximate the mean value  of 220  VP/day  obtained  from  the data  in
Section 2.1.   All traffic  occurred  at a nominal speed of  24 kph (15 mph).

     The east and west  ends  of the  road (including  the turnarounds) were
treated as buffer areas.   Roughly 25% of  the total  load of each chemical
(excluding calcium chloride which was applied by  the  delivery  truck)  was  !
used on the  test  section and  the remainder  applied  to the buffer areas
(Generic and  Soil Sement at the  east end, Petro Tac and  Coherex® at  the
west).  Buffers between individual test sections were formed by overlapping
chemical applications (excluding  calcium  chloride) by approximately 10 m.
These buffers were routinely swept to reduce track-on and were periodically
retreated using a new dust suppressant supplied by Syn Tech Products Corpo-
ration.

3.3  CONTROL APPLICATIONS

     MRI supervised the application of all  chemicals (both  test sections and
buffer areas) during  this  field program.   Measurements  of  application  rate
and density were taken whenever test sections were treated.  Tables 3-1 and
3-2 present  the application parameters for plants AP and AQ,  respectively.

     The test sections were characterized  in terms of silt  content and total
loading prior to treatment.  Summary data are given below:


                              Mean Values of                                !
                  Pre-Application Surface Characteristics
                                       Plant AP          Plant AQ
          Total loading (g/m2)          9,400             1,200
          Silt content (%)                  8.0              13.9
          Silt loading (g/m2)             750               170
                                  37

-------
                  TABLE 3-1.  APPLICATION PARAMETERS - PLANT AP

Chemical
Petro Tac
Coherex®
Calcium chloride
Test
strip
1
2
3
Dilution Application intensity, L/ra2 (gal/yd2)
ratio 5/1785
5:1 2.0 (0,44)
5:1 2.5 (0.56)
a 1.1 (0.25)
S/6/85
1,0 (0.23)
1.0 (0.22)
0.86 (0.19)
6/14/85
3.8 (0.83)
4.5 (1.0)
1.7 (0.38)
7/2/85
-
.
1.5 (0.34)

As received (38% solution).

Application of 6/14/85 largely washed off due to heavy rains shortly
after completion.   Delays in scheduling distribution truck and un-
favorable meterological conditions postponed reapplication until 7/2/85.
                  TABLE 3-2.   APPLICATION PARAMETERS - PLANT AQ

Chemical
Calcium chl
Coherex®
Soil Sement
Generic
Petro Tac
Test
strip
oride 5
4
3
2
1
Dilution Application
ratio
a
5:1
5:1
5:1
5:1
7/26/85
1.1
0.95
0.72
0.63
0.95
(0-
(0.
(0.
(0.
(0.
24)
21)
16)
14)
21)
intensity, L/m2 (gal /yd2)
9/3/85
1.3
1.6
2.0
2.1
1.6
(0
(0
(0.
(0.
(0.
.29)
.36)
44)
46)
35)
10/17-21/85
2.3
7,2
1.3
7.7
7.7
(0.
(1.
(0.
(1,
(1.
51)
6)
28)b
70)c
70)

a As recei

ved (38% sol

ution).




Kir



f-*r-¥t







T2sn4"

214- "1 ua
    c  Dilution ratio of 12:1, following recommendations of Mellon Institute.
                                      38

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Figure 3-3  shows  the  variation of these  surfaces  parameters  over the  two
test roads.

3.4  RESULTS OF THE EXPOSURE PROFILING TESTS

     Sixty-four exposure profiling tests of unpaved road dust emissions were
conducted during the course of this study.  Site parameters associated with
these tests are  presented  in Tables 3-3  and  3-4.   Several remarks about
these tables are in order.

     First, each test is identified by a run number composed of a plant pre-
fix, a sequential identification number and finally, a road section suffix.;
The suffix  serves to  identify  the  type of control  applied  to  the  road  seg-
ment.   The letter "U" indicates an uncontrolled surface.  In addition,  each
suppressant has been assigned a code letter as follows:


                                                 Test section
          Code letter    Suppressant         Plant AP    PI ant AQ

              P          Petro Tac              1           1
              G          Generic                -           2
              S          Soil Sement            -           3
              X          Coherex®               2           4
              C          Calcium chloride       3           5
     Code letters are used hereto discourage selective citation of test re-
sults.  Because the selection of a dust control product necessarily entails
evaluation of both performance characteristics and cost considerations (such
as capital equipment costs), no individual table of results taken from this
report can provide all the  information  required.   Therefore,  the reader  is
strongly cautioned against taking any results out of context.  The report as
a whole provides a better basis for decisions than does any single data set.

     Secondly, four  tests (AP-1) wert performed  using  the  abbreviated  sam-
pling array discussed in Section 2.0.  In these tests, upwind concentrations
were larger than three of the four downwind values.  Much of the difficulty
associated with the abbreviated array at plant AP stemmed from the very ir-
regular flow patterns caused by surrounding structures.  No further attempts
were made to  use the abbreviated array  at  this  plant.  Although plant AQ
would have proved more amenable to the abbreviated sampling array, the ori-i
entation of the  road to  prevailing wind  direction  and  the  site's proximity
to MRI's main laboratories made this array unnecessary.                    ••

     No tests  of calcium chloride took  place  at plant AP  after run AP-3.
The shorter lifetime of calcium chloride compared to the other two chemicals
made  it  difficult to avoid possible contamination of adjacent sections.  ;
                                  39

-------
 0
                 TOTAL

 j
 ?
      /
     as
      o
      0  I-
                 3/t.T CONTENT
               i     2     3
            AP   T£ST
AQ    T£ST
Figure 3-3.  Variation of surface material properties (before control) over
              test sections  (see text for mean values).
                                 40

-------
TABLE 3-3,   TEST SITE PARAMETERS - PLANT AP
- 	 „_. " "' "" 	 	 — 	 	
Ambient .
tempera tt
Run Date (°C)
API PJJ 5/07/85 21C
X.
Cb
UD
AP2 P 5/09/85 21C
X
C
U
APS P 5/10/85 21C
X
C
U
APS P 8/17/86 23
X
AP6 P 8/19/85 24
X
U
AP7 P 8/23/85 22
X
U
air Mean
jre wind speed*1
(8./S)
-
-
-
—
4.8
3.4
1.9
1.9
4.9
3.8
3.8
2.8
1.2
1.7
0.91
1.6
1.6
0.41
0.72
0.72
(mph)




11
7.6
4.2
4.2
11
8.5
8.5
6.2
2.6
3.9
2.0
3.7
3.7
0.92
1.6
1.6
les,l
start Duration
time (min)
1227
1227
1227
1227
903
903
903
904
850
850
850
850
945
943
1437
1440
1450
825
821
823
10
27
76
37
128
128
128
127
119
119
119
119
84
82
59
56
46
104
109
87
Niimliiir of
VL'tllt: lu
passes
8
16
48
19
68
68
65
8
50
50
50
10
34
34
51
51
51
87
90
85
tfujilc ju_ wulylil
27
26
26
29
24.6
24.6
25.5
30.0
26.4
26.4
26.4
33.7
25.5
25.5
23.7
23.7
23,7
23.7
23.7
22.8
30
28
29
32
27
27
28
33
29
29
29
37
28
28
26
26
26
26
26
25
Avurti(|i> Nil,
J»t WllUltlb
15.5
14.9
15.4
15.0
12.3
12.3
11.8
7.0
7.08
7.08
7.08
5.20
13.9
13.9
17.4
17.4
17.4
13.5
13.4
13.4

Measured at 4.5 m height
Abbreviated array.
Estimated value.
just prior


to, during,




and immediately after




tests.









-------
TABLE 3-4.  TEST SITE PARAMETERS - PLANT AQ

Ambient air Mean
temperature wind speed
Run Date (°C)
AQ1 U 9/16/85 28
G
S
X '
AQ2 U 9/16/85 28
G
S
X '
AQ3 P 9/17/85 24C
G
S
X
AQ4 G 9/17/85 24C
S
X '
c
AQ5 P 10/02/85 17
G
S
c ••
AQ6 P 10/02/85 24C
------ G 	 - - .. _ 	
S
C
(m/s)
3.8



3.9



5.1
4.0
4.0
4.0
4.9
4.5
5.2
5.8
2.6



2.2



(mph)
8.4



8.7



11
9.0
9.0
9.0
11
10
12
13
5.9



5.0d



Test
start
time
1025
1024
1012
1015
1241
1229
1226
1229
954
943
945
948
1630
1531
1720
1535
1055
1208
1045
1054
1537
1436
1436
1436
Duration
(MI in)
64
66
75
75
69
82
85
82
105
52
50
47
22
28
22
33
21
20
29
20
18
28
23
23
Number
'of vehicle
passes
50
50
50
50
68
68
68
68
76
19
19
19
50
50
50
50
34
34
34
34
44
36
36
36
Average
vehicle weight
(Kg)
9.1
9.1
9.1
9.1
8.9
8.9
8,9
8.9
8,8
S.5
8.7
8.7
22
22
22
22
22
22
22
22
22
22
22
22
(ton)
10
10
10
• 10
9.8
9.8
S.8
i.8
9.7
9.3
9.6
9.6
24
24
24
24
24
24
24
24
24
24
24
24
Average No.
of wheels
6.0
6.0
6.0
6,0
5.9
5.9
5.9
5.9
5.9
5.8
5.9
5.9
6.0
6.0
6.0
6.0
5.9
5.9
5.9
5.9
6.0
6.0
6.0
6.0
                 (continued)

-------
                                                TABLE 3-4 (continued)
4s.
Co

Ambient air Mean Test Number Average
temperature wind speed start Duration of vehicle vehicle weight Average No.
Run
AQ7


"j
u
AP8



AP9



AP10
»


Apll




P
6
S
x-

P
G
S
X.1
G
S
X1-'
C'
G
S
X
c
G
S
X
c
Date (°C)
10/03/65 18




10/03/8& 21



10/25/85 18



11/05/85 16



11/05/85 13



(m/s) (mphj time
2.9 6.5d 1149
1245
1150
1150

2.2 5.0d 1558
1520
1518
1518
2.9 6.5 1117
1117
1143
1124
2.9 6.6 954
954
954
1000
3.9 8.7 1349
1349
1349
1348
(mm)
30
25
28
28

22
16
17
17
110
110
62
267
138
134
129
133
127
127
130
130
passes
50
48
50
50

36
34
34
34
125
125
79
125
200
200
200
200
250
250
250
250
(Hg)
22
22
22
22

22
22
22
22
9.
9.
9.
9.
6.
6.
8.
6.
5.
5.
5.
5.









1
1
1
1
9
9
9
9
9
9
9
9
(ton) of wheels
24
24
24
24

24
24
24
24
10
10
10
10
7.6
7.6
7.6
7.6
6.5
6.5
6.5
6.5
6.
6.
6.
6.

6.
6.
6.
6.
6.
6.
6.
6.
5.
5.
5.
5.
5.
5.
5.
5.
0
0
0
0

0
0
0
0
0
0
0
0
3
3
3
3
0
0
0
0

a 4.
5-m
During
equivalent prior to,
profiler ooeration.
during and after tests,

except as

noted.











3 * ~ • — -_...._- _ 	 „, 	 — 	 ___
c Estimated value.
d 3.0-m
height.









-------
    .C
    O
20 —
         15  —
Ul    0
    0
          IO
          O  ~"~
          O
             Jw/y     Au^os"}      September
           Figure 3-4.  Cumulative rainfaU  and
                                                      of
                                                                        at pUr.i

-------
Furthermore, as  noted  in Table 3-1, the treatment  of  June  14 was  largely
washed off by heavy rains a few hours after application.  Problems in sched-
uling the distributor truck and unfavorable meteorological forecasts delayed
reapplication.   It appeared that at least the section treated with Colierex®
was contaminated during  the 2  weeks between  applications.   The decision  to
abandon the  C  test strip and to treat both this strip and the surrounding
buffers as  part  of the plant's Petro Tac rotation was made in conjunction
with the project officer.

     Further difficulties were encountered with  standing  water and rutting
of the road at plant AP.   The first 2 weeks of August produced 100% of nor-
mal precipitation for the month.   The south sides of the X test section and
of the buffer were found to be badly rutted once the water was removed.  To
ensure safe  vehicle operation and  to  reduce spillage, these  areas were
slagged and treated with Petro Tac.   All subsequent tests restricted traffic
to the north side of the road.

     During the same period, the uncontrolled section at plant AP also con-
tained standing water.   After  drying,  the surface resembled caked mud and
was not representative of the road prior to application of controls.

     Finally, testing  at plant AQ was  hampered by one  of  the  wettest falls
on record.   Figure 3-4  compares the 1985  precipitation record with the
cliiatological  record; in  addition,  important events are noted along  the
time line.   During the four months  after the  initial control  applications,
recorded rainfall represented 224,  160, 306, and 263% of normal.  The,heavy
rains of mid-October caused flooding in areas surrounding the test site and
all sampling equipment was  moved to higher ground.   Standing water during
this period caused severe rutting in the P test section.  Regrading was nec-
essary for safe vehicle operation;  this, however, required that the surface
be abandoned for further testing.  After regrading, this segment was heavily
retreated periodically as were the other buffer areas.                !

     Tables 3-5 and 3-6 compare,  for each run, raw concentration values both
upwind and  downwind of the test  road.   It should be  noted that direct  com-
parison of  TP  concentrations measured  by the  profiler  and cyclone/impactor
samplers is  hindered by  the fact that  the latter units  were often  operated
for a  longer time  period to obtain  adequate  sample  mass on  each substrate.

     Table 3-7 and 3-8 gives measured wind speeds and isokinetic flow ratios
for the profile  or sampling heads.   These  values,  in  conduction with  the
aerodynamic  particle size  data presented in  Tables  3-9  and  3-10, were  used
to determine isokinetically corrected TP concentrations as needed, using the
procedure described in  Section 2.7.  Note that some tests at plant AP are
characterized by wind speed profiles which decrease with height.   It is be-
lieved that this is the  result of irregular flow patterns due to surrounding
obstructions.
                                  44

-------
    TABLE 3-5,   REPRESENTATIVE CONCENTRATIONS3 (Mg/m3) - PLANT AP
•••••••IMHi
Run
AP2



AP3



APS

AP6


AP7


P 	
P
X
C
u
P
X
C
u
P
X
P
X
u
P
X
u
Upwind hi-vol
5S2
1,660
1,020
609
357
537
371
796
705
487
2,200
2,590
1,190
284
209
535
Downwind cyclone
421
483
787
1,130
277
364
503
1,040
3,830
6,730
7,330
12,400
2,080
12,800
5,610
12,800
Downwind profiler
721 ;
810^
736C
1,520
545
554 i
508
1,400 1
2,890 1
5,250 ''
5s400d
9,740
2,830 ]
6,160 I
3,730 i
7,330 !
a  At 2.2-m height,  except as noted.
b  Interpolated from profiler heads nearest 2.2-m height.
c  1,5-m value.
d  Estimated value.
                                  46

-------
TABLE 3-6,  REPRESENTATIVE TP CONCENTRATIONS3 (»g/m>) -
4Q
Run Upwind hi-vol Downwind cyclone
AQ1 U
G
5
X
AQ2 U
G
S
X
AQ3 P
G
S
X
AQ4 G
S
X
C
AQ5 P
G
S
C
AQ6 P
G
S
C
AQ7 P
G
S
X
AQ8 P
G
S
X
AQ9 G
S
X
C
AQ10 G
S
X
C
AQ11 G
S
X
C
54
54
54
54
54
54
54
54
121
121
121
121
121
121
121
121
190
190
190
190
190
190
190
ISO
112
112
112
112
112
112
112
112
32
32
32
32
63
63
63
63
63
63
63 '
63
a At 2.2-m height, except as
Interpolated
from profiler
2,340
1,330
741
2,300
2,340
1,330
741
2,300
709
i93
567
1,170
4,730
3,480
6,610
5,320
§,790
3, §70
3,560
7,860
6,860
5,970
9,810
13,500
5,720
2,980
2,770
8,750
3,270
4,190
3,090
3,210
670
126
278
171
863
301
330
230
863
301
330
227
noted.
heads nearest 2.2-m
Downwind profile^
2,810
3,020
1,280
5,330
3,050
2,320
647
2,300C
1,330
453
299
318
22,600
7,080
14,800
8,480
14,100
6,040
6,780
23.600
22,800
9,840
7,030
22,800
3,990
4,560
6,130
12,700
5,900
5,300
6,390
15,800
856
230
181
121
1,170 ,
40 7d
343
453
1,600
452
387
378

height..
c Estimated value.
3.0-m value.




47



-------
     TABLE 3-7.   ISOKINETIC CORRECTION PARAMETERS - PLANT AP
                     Wjnd speed	         Profiler
1.5 m
Run
AP2



AP3



APS

APS


AP7



P
X
C
u
P
X
C
u
P
X
P
X
u
P
X
u
(cm/s)
167
149
130
158
305
283
283
266
168
165
167
173
168
48
67
63
(fpm)
328
294
256
312
600
558
558
524
330
324
328
341
330
94
132
124
4.5 m
(cm/s)
486
339
206
197
481
372
395
268
117
179
90
160
149
40
73
68
(fpm)
957
667
406a
387a
947
732
778*
528a
231
352
178
315
294
78
143
134
isokinetic flow ratios
1.5 m
1.59
1.40
1.01
1.01
1.02
1.00
0.86
1.00
0,57
0.86
1.02
0.93
0.95
4.34
1.73
1.53
3 m
0.85
-
-
0.96
0.99
1.22
1.23
0.99
0.44
0.92
1.29
1.00
1.02
2.42
1.84
1.46
4-5 m
0.68
1.13

-
1.04
1.42

-
0.74
0.93
1.89
1.06
1.11
2.80
1.56
1.70
6 m
0.74
1.03
2.09
1.03
1.03
1.36
1.44
1.15
0.78
0.93
3.51
i.ii
1.04
3.83
1.41
1.41

6.0-m value.
                               48

-------
TABLE 3-8.  ISQK1NITIC CORRECTION PARAMETliS - PLANT AQ
Wind speed
Run
AQ1



AQ2



AQ3



AQ4



AQ5



AQ6



AQ?



AQS



AQ9



AQ10



AQ11




U
G
S
X
U
G
S
X
P
G
S
X
G
S
X
c
P
G
S
c
P
G
S
c
P
G
S
X
P
G
S
X
G
S
X
C
G
S
X
C
G
S
X
c
1.5
(CBI/S)
115
115
113
114-
235
228
225
225
252
277
281
287
247
144
250
280
215
206
200
222
104
171
189
189
182
192
175-
175
148
143
142
142
163
163
186
16S
109
110
111
110
178
178
175
177
m
(fpra)
226
226
222
224
463
448
443
443
496
546
554
565
487
283
493
551
424
405
394
438
205
337
372
372
359
378
345
345
291
282
279
279
321
321
366
326
215
216
218
217
350
350
344
348
4.
(cmh)
458
4S8
440
445
389
401
384
386
504
465
468
473
494
443
497
559
356
233
348
374
190
313
345
345
331
367
321
321
271
247
241
241
287
287
326
286
292
294
294
295
379
377
383
378
5 f»
(fpm)
902
901
866
876
766
789
756
759
992
915
922
932
973
872
978
1100
700
458
686
737
374
617
680
680
652
722
632
632
533
486
475
475
565
565
641
563
574
578
578
582
747
742
763
744
Profiler
isokinetic
1.5 m
1.01
1.01
1.03
1.02
1.06
0.97
0.98
-
1.16
0.66
0.72
1.81
1.54
2. OS
1.28
1.44
0.76
0.95
0.75
0.74
2.11
1.28
1.06
1.16
0.89
1.03
0.91
0.91
1.48
1.53
1.42
1.29
0.99
0.99
1.01
1.04
1.03
1.04
1.21
1.02
1.03
1.03
1.05
1.03
3 m
0.67
0.67
0.70
0.68
0.91
0.91
0.91
-
O.il
0.79
0.78
m
1.07
1.13
0.88
1.00
0.82
0,97
0.69
0.78
1.62
0.98
0.70
0.70
0.88
1.02
0.90
0.90
1.14
1.38
1.36
1.36
0.94
0.94
0.95
1.01
1.01
1.09
0.97
1.00
0.46
1.04
1,01
1.01
flow ratio
4.5 »
0.63
0.63
0,67
0.65
0.97
0.87
0.96
0.9S
0.80
-
0.36
0.85
1.05
1.05
0.74
0.98
0.86
0.98
0.71
0.82
1.25
0.76
0.69
0.69
0.86
0.79
0.90
0.90
1.01
1.27
1.34
1.34
0.94
0,94
0.98
J.OO
1,01
0.83
1.12
-
1.02
1.03
1.04
1.02
6 a
0.60
0.60
0.64
0.6?
1.01
-
1.00
1.00
0.87
-
0.38
0.88
0.9-3
0.98
0.80
0.91
0.86
1.00
0.75
0.8?
1.20
0.71
0-3
-------
       TABLE 3-9.   AERODYNAMIC PARTICLE SIZE DATA - PLANT AP

Percent less
Run
AP2



AP3



APS

AP6


AP7



P
X
C
U
P
X
C
U
P
X
P
X
U
P
X
U
% < 15
UW
88
85
36
82
84
84
84
87
67
75
72
76
. 71
79
74
76
ym
OW
19
32
34
42
31
31
40
42
28
24
28
31
42
11
14
18
%
UW
83
80
81
76
79
79
78
83
57
70
64
S3
62
73
68
63
than stated size !
< 10 ym
DW
15
25
28
34
26
26
35
34
22
19
22
24
31
9
12
13
% <
UW
60
61
57
53
56
56
51
62
22
50
32
36
29
54
50
26
: 2.5 MBI
DW
6
i 10
11
10
14
ill
16
:i3
; 8
; 7
; 6
i 8
7
'• 3
4
• 4
a  UW denotes upwind, DW downwind.
                                    50

-------
         TABLE  3-10.  AERODYNAMIC PARTICLE SIZE DATA - PLANT AQ
Run
AQ1



AP2



AQ3



AQ4



AQ5



AQ6



AQ7



AQ8



AQ9



AQ10



AQ11




U
G
S
X
U
6
S
X
P
G
S
X
G
S
X
c
p
G
S
c
p
G
S
C
p
6
5
X
P
G
S
X
G
S
X
c
G
S
X
c
G
S
X
c

i <
UW
93



93



87



87



96



96



85



85



100



86



86



Percent
15 urn
ow
24
26
18
12
24
26
18
12
29
20
20
9
19
17
10
8
21
22
20
24
17
17
18
22
16
21
15
20
2S
27
24
2S
34
38
28
31
34
38
28
32
34
38
28
32
less than
% < 10
UW
86



86



62



62



88



88



58



S8



100



75



75



stated sizea
Mm % < 2.5 t
DW UW
17 66
21
14
10
17 66
21
14
10
26 45
16
16
7
15 45
13
7
7
17 85
18
16
li
12 85
12
14
16
12 48
16
10
14
18 44
21
18
19
26 100
29
20
22
26 42
29
20
24
26 42
29
20
24

in
ow
4
Q
5
3
4
9
5
3
16
6
6
2
6
4
2
2
7
6
6
7
3
3
5
6
4
c
2
5
S
3
4
7
7
6
S
5
7
5
5
7
7
6
5
7
3  UW denotes upwind, DW downwind.
                                    51

-------
     Individual point values  of  isokinetic TP exposure (net mass per sam-
pling intake area) within the open dust source plume are presented in Tables
3-11 and 3-12.   These are values integrated over the height of the plume to
develop emission factors, is discussed in Section 2.0.

     Tables 3-13 and 3-14 present size-specific emission factors for plants
AP and AQ,  respectively.  Also shown  in these  tables are surface aggregate
material  properties.  These values have been normalized using the procedure
described in Section 2.7.

     Finally,  mean  uncontrolled normalized emission factors  for  the two
plants were obtained in order to determine control efficiency;         '


                   Mean Normalized Uncontrolled Emission               <
                             Factors (g/VKT)a
                               Parti cle size fraction
                  Plant     TP       IP      PM10     FP
AQC
8,850
3,690
1,860
821
1,510
561,
186
101

                     Normalized to 25 Mg (28 tons) and
                     12 wheels for plant AP, and 9.1 Mg                •:
                     (10 tons) and 6 wheels for plant AQ.               1
                     All tests were conducted with a
                     nominal 24-kph (15-mph) average ve-               ;j
                     hide speed.

                     Only runs AP-2 and -3 used because
                     later tests were characterized by
                     muddy and caked surface.

                  c  Corrected to average silt content of              ;
                     treated sections before application.


     Several remarks about  these  mean values are in order.   First, it was
necessary to correct the AQ uncontrolled emissions to reflect the silt con-
tent of the treated sections before application.                       ;
                                  52

-------
               TABLE 3-11.   PLUME SAMPLING DATA - PLANT AP

Run
AP2



APS



APS

AP6


AP7



P
X
C
U
P
X
C
U
P
X
P
X
U
P
X
U
Safflpl
1.5 m
37
36
24
27
29
26
23
25
17
25
30
28
28
35
20
17
inq rate (m3/hr)
3 m
57
-
-
30
38
38
38
25
11
28
29
29
29
19
23
17
4.5 m
60
70
-
—
46
49
-
-
IS
29
30
30
29
20
20
20
6 ffl
77
76
75
36
50
52
52
28
13
30
32
30
32
24
18
17
Net TP exposure3 (mg/cm2
1,5 m
0.457
0
0
1.33
0.527
0.271
0.510
1.34
2.15
4.02
3,13b
4.47
0.617
1.54
1.83
2.29
3 ID
0
0
0
0.952
0.380
0
0.0194
0.955
1.27
3.87
2.23.
3.66b
0.877
1.84
1.29
2.08
4.5 m
0
0
0
(0.809)
0.0647
0
(0.00970)
(0.619)
0
3.26
1.10b
1.87
0.517
0. 764
0.624
1.04
)
6 m
0 :
0 :
0 i
0.665 ;
0
0
0
0.283
0.462
1.51 :
0.0348b
0.336
0.215
0.280
0.227
0.803

Values in parentheses are interpolations.  Zeroes indicate no net mass
flux.

The filters for this run were lost; these estimates are based on scaling of
profiler wash catches by cyclone TP concentration.
                                   53

-------
             TABLE 3-12.   PLUME SAMPLING DATA - PLANT AQ
Sampling rate (wVhr)
Run
AQl



AQ2


AQ3



AQ4



AQ5



AQ6



AQ7



AQ8



AQ9



AQ10



AQ11




U
G
S
X
U
G
S
X
p
G
S
X
G
S
X
c
p
G
S
c
p
G
S
C
P
G
S
X
p
G
S
X
G
S
X
c
G
S
X
c
G
S
X
c
1.5 m
20
20
20
20
23
20
20
27
17
19
48
35
27
30
37
27
34
25
27
20
20
19
20
29
35
28
28
20
20
19
17
28
28
33
30
20
20
23
19
32
32
32
32
3 m
39
39
39
39
28
28
27
35
29
29
-
40
34
33
43
42
38
36
43
24
24
19
19
43
53
42
42
24
26
25
25
40
40
46
43
40
43
35
40
26
56
54
54
4.5 n
51
51
51
51
35
32
34
34
38
-
37
37
48
43
34
51
53
40
44
53
22
22
22
22
50
51
51
51
26
28
29
29
47
47
56
50
52
42
57
"
36
36
37
36
6.m
58
58
53
58
40
-
39
39
46
-
43
43
51
47
42
54
59
42
51
59
24
24
34
24
59
70
56
58
27
31
-
36
.
49
60
54
61
-
-
61
40
-
-
40
Met TP exposure3 (nig/cm*)
1.5 in
1.80
2.29
0.992
4.34
4.02
3.06
0.982S
(3.10)b
2.78
0.341
0.256
0.189
10.5
2.39
6.72
6.43
4.91
1.66
3.07
7.91
3.43
3.55
2.32
7.70
1.61
1.18
2.24
5.03
1.63
0.586
1.03
3.10
1.36
0.317
0.152
0,379
1.48
0
0.453
0.539
2.69
0.980
0.690
0.641
3 m
1.60
0.848
0.593
2.45
2.38
2.81
0.491.
(2.60)°
1.56
0.324
0.218
(0.178)
6.23
2.03
4.43
4.24
3.56
1.30
2.08
6.28
2.34
2.90
1.79
5.85
1.35
2.13
1.89
3.41
0.867
1.23
1.10
1.87
0.529
0.143
0.0693
0.112
0.957
0.628
0
0.252
2.42
0.0274
0.216
0.346
4.5 m
0.815
0.0691
0.133
0.533
0.797
0.156
0.278
0.841
0.692
(0.0610)
0.104
0.104
1.93
0.980
1.60
0.634
2.30
0.395
0.933
2.47
0.904
1.73
0.644
2.25
0.547
0.854
0.755
1.12
0.306
0.378
0.564
0.523
0.219
0.0436
0
0.0550
0.350
0.122
0
(0.142)
0.561
0.0460
0
0
6 m
0.242
0
0
0.0888
0.391
0
0
0.092
0.194
0
0
0.0760
0.800
0.334
0.487
0.137
0.836
0.0872
0.388
0.295
0.383
0.635
0.300
0.418
0.153
0.320
0.179
0.0535
0.188
0.0828
0
0
0
0.0169
0
0
0.116
0
0
0
0.178
0
0
0
Values in parentheses are Interpolations; zeros indicate no net (i.e.,
downwind minus upwind) contribution.

These values based on linear interpolation/extrapolation using cyclone
and 4.5-m profiler values.

                                  54

-------
              TABLE 3-13.   SURFACE PROPERTIES AND EMISSION FACTORS - PLANT AP

AP2 P
X
C
U .

APS P
X
C
U

APS P
X
AP6 P
X
ue
AP7 Pf.
XI
ue
Silt
content
(X)
1.9
d
2.7
8.1

2.6
d
4.3
8.3

6.1
11
6.8
10
7.3
11
12
6.0
Moisture
content
(X)
0.46
0.50
1.2
0.64

0.36
1.4
1.4
1.1

0.12
0.14
0.13
0.08
0.10
-
-
~
Total
1 oadi ng
(kg/o*)
6.4
0.73
5.4
6.7

8.5
0.88
4.6
6.3

4.8
2.0
8.7
5.1
2.0
_
-
2.09
Emission factor (a/VKT)3 <
Rawb
TP
179
-
.-
9,110
y- ' '
369
145
279
5,920
7-- •-'
2,330
6,460
1,480
3,720
711
877
346
1,430
*—
TP
182
-
-
10,600

468
184
355
7,390

2,170
6,010
1,290
3,240
620
871
843
1,470
.'Normal
IP
21.4
-
-
2,230
""''
55.3
30-5
-
1,550
5". : '-
412
1,200
118
620
18.0
81.8
101
220
1zedc
PMio
13.5 ,
-
-
1,810 :
- r - 'i
35.0
22.0
;
1,260 ;
- • '"•"
305
902
50.2
389
•B
65.1
82.6
162 '

FP
5.33
-
-
223
-'
13.8
3.07
-
155
"-
104
216
-
19.5
—
15,7
18.6
44.0

   Blank entries denote cases of no net mass detected.

   Because the normalization process does not affect size fractions, raw emission  factors
   for the other size ranges can be obtained by scaling the normalized values by the ratio
   of the TP results.

c  Normalized to 25 Mg (28 tons) and 12 wheels per vehicle.

d  Less than 0.05%.

e  These tests were characterized by a muddy and caked uncontrolled surface.  See  discus-
   sion in text.

   These sections had been flushed and vacuumed 3 days prior to test.  See discussion  in
   Section 4.0.

"  Estimated value.
                                              55

-------
           TABLE 3-14,  SURFACE PROPERTIES AHO EMISSION FACTORS - PUNT AQ


Un.1 «4>t.w.M
^ ) i w rru , 9 ^ui V
content content

AQ1 U
S
S
X

AQ2 U
G
S
X
Aq3 P
G
S
X
AQ4 G
S
X
c
~AQS P
G
S
C
AQ6 P
G
S
_ c
AQ7 P
G
S
X
AQ8 P
G
S
X
AQ9 G
S
X
c
AQ10 G
S
X
C
AQ11 G
S
X
c
a Blank
E$ar»ait«
(X)
7,0
7.6
0.6
15

7.0
7.6
0.6
15
3.1
6.8
1.5
12
6.8
1.5
12
•*
5.0
10
4,4
12
5.0
10
4,4
12
3.6
7.0
2.9
6.7
3.6
7.0
2.9
6.7
0.76
1.2
1.1
1.6
2.9
-
-
-
2.9
->
-
"
entries
*A i>K*k «t#
T«*«1
Emission factor 
-------
The five treated sections had a preapplieation average silt content of 13.9%
with a standard deviation of 2.2%.  However, the uncontrolled tests at this
site were characterized  by  a  silt content  of approximately  7%.   This  lower
value may be the result of different drainage characteristics at the uncon-
trolled section.  Because  uncontrolled particulate emissions from unpaved
roads show  a  linear  relationship  with  silt content,6  the  mean  uncontrolled
test results were scaled linearly to reflect a silt value of 13.9% in order
to relate control efficiency to the preapplication state.

     Secondly, because of the muddy and caked conditions found on the uncon-
trolled surface at plant AP during August 1985, only the AP-2 and -3 uncon-
trolled tests were used in determining mean values.
                                  57

-------
                                SECTION 4.0

                       CONTROL EFFICIENCIES AND COST
                           EFFECTIVENESS VALUES
     This section uses  the  test results given in the preceding section to
develop control efficiency  and  cost-effectiveness values for the chemical
dust suppressants evaluated.  Particular attention  is paid  to average  con-
trol efficiency values  which  are required to estimate emission reductions
and cost-effectiveness.   In addition,  a discussion of control performance
indicators based on surface material properties is also presented.

     It should be noted that this discussion is limited to the AQ series of
tests.   As noted in preceding sections, the AP series was hindered by numer-
ous problems and,  as a result, only a small number of tests was performed at
that site.  Furthermore,  because all five  chemicals were  evaluated concur-
rently at the AQ site,  consideration of only tests  at this  site  simplifies
comparisons.                                                           !

     One important finding from the AP test series, however, should be men-
tioned.  Run AP-7 was conducted on test surfaces which had been flushed and
vacuumed 3 days earlier.  A control efficiency of 90% or more was found for
all size ranges considered.   Thus,  it would appear that paved road cleaning
techniques may be  used to periodically increase the control efficiency of
chemically treated unpaved roads.

     Control performance was examined in terms of several nonparametric sta-
tistical tests.10  A  10%  level  of  significance  (a = 0.10) was selected for
comparisons involving  only  one  chemical;  for comparisons ipvolving two or
more chemicals, a was set equal  to 0.05 (5%).

     Finally, calcium  chloride  is  included only in  the discussion of cost-
effectiveness.  The rationale for  this  decision is  based  on the  facts  that
this product  is not commonly  used  in the main  iron  and steel  districts and
that,  on  the  basis  of the two test series, this product may not exhibit a
control lifetime similar to the other four suppressants evaluated.

     The difficulties encountered due to the washoff of calcium chloride at
plant AP were described in Section 3.4.  In addition, the heavy rains during
the second half of September may have seriously affected the control perfor-
mance  of  calcium chloride at  plant AQ;  emissions  at the  uncontrolled level
were found at the end of 1 month.  However, it  is important to note that the
test results from late October and early November show that calcium chloride
provided a level of control easily the equal of the other three suppressants.
During this  time,  the calcium chloride test  section  appeared visibly  wet
even after 3 to 4 hr of steady traffic.                                '

                                  58

-------
4.1  COMPARISONS INVOLVING ONLY ONE CHEMICAL

     This section presents a discussion of comparisons of point (instantane-
ous) values of  control  efficiency  for  a single  dust  suppressant.   The  most
important comparison involves temporal  dependence of control efficiency be-
cause the results obtained determine the functional forms for c(t) and C(T),
as defined in  Section  2.7.   In cases  of significant decay  with time,  in-
stantaneous and  average control efficiency are  treated as linear  functions
of time.  Otherwise, average efficiency is considered as a constant value
over the time period of interest.                                           I

     Other comparisons  involving  a single dust  suppressant are  also de-
scribed.  These examine whether there  is a significant difference in a prod-
uct's control performance for  various  size fractions and whether  a  repeat,
higher intensity application results in a higher level  of control.

     To assess  the  time dependence of  control,  the results  of  runs  AQ-1  to
-4 were compared to those of AQ-5  to  -8.  These two groups of tests were
conducted at 13  to  14  and 29  to 30 days after  application,  respectively.
The Mann-Whitney U test11 was employed to determine whether control perfor-
mance for a given chemical decreases with time over the first 30 days after
application.   The results of the comparisons for TP and PM10 are shown below:


                                             Significant
                                             decrease in
               Chemical    Size fraction       control                      :

                   P          TP                 no                        :
                              PM10               no                        ;

                   G          TP                 no                        ;
                              PM10               no

                   S          TP                 yes
                              PM10               yes

                   X          TP                 no                        ;
                              PMio               yes
             3  One-tailed alternative hypothesis.                        \


Only three comparisons  showed  a  decrease  (significant  at  the  10% level)  in
control over the  time period of  interest.   As  noted  earlier,  this  informa-
tion was  used  to  determine the  forms  for the  average control efficiency
functions presented in the next  section,                                  ;
                                  59

-------
     A U test of the results from runs AQ-1  to  -4  and  AQ-9  to  -11  wag  also
performed.   Because all these ttsts were conducted at approximately the same
time after application, this comparison tested whether there was a signifi-
cant increase in control after the repeat application in October.  All com-
parisons showed increases significant at the 5% level.

     To determine  whether control efficiency  is  significantly different
for various  size ranges,  a two-way analysis  of  variance  by  ranks (Friedman
test11) was employed with a two-tailed alternative hypothesis.   Of the four
chemicals,  only Soil Sement exhibited a significant (a = 10%) difference in
control between the TP, IP and PM10 siii fractions during the period of runs
AQ-1 through -8.  No significant differences were found for runs AQ-9 through
-11.                                                                 I

4,2  AVERAGE CONTROL EFFICIENCY                                      :

     Least-squares lines  of best fit were developed for  those  suppressant/
size  fraction  combinations  which showed  significant  temporal  dependence
over the period of AQ-1 to -8.  Average control efficiency functions were
then determined from the lines of best fit.   In instances where no signifi-
cant difference with time was  found, all control  efficiency values were
averaged and the mean value applied over the period of the first eight runs
(i.e., first 13 to 30 days after application).

     Figure  4-1 presents average, size-specific control  efficiency as a
function of  time for the  four  dust suppressants.   Because of the nature of
the field  program  conducted  at plant AQ, these functions may be viewed as
representative  of  typical values  of  application and dilution rates, daily
traffic volume and average vehicle weight for unpaved roads in the iron and
steel  industry.  Furthermore,  because  most plants in the industry reapply
chemicals within 1 month  (cf  Table 2-1), these average control efficiency
functions  should be of considerable  use to both iron and steel  and regula-
tory  agency  personnel   in assessing  the emission  reductions and  cost-
effectiveness of dust control  programs.

     As can  be  seen from the  figure,  average control  values for the four
dust suppressants  tend to be more closely clustered for the IP and PM1(> size
fractions than for the two extreme size ranges  (TP and FP).   The question of
whether there is a significant difference in control performance between the
various suppressants is addressed in the following section.           '•

     As a final remark, it should be noted that these results are based upon
field tests after a second control application.   Thus, some residual effect
of the initial application is  included.  A further discussion of the effect
of repeated applications on average control efficiency is presented in Sec-
tion 5.0.

4.3  INTERCHEMICAL COMPARISONS

     The results given as Figure 4-1 indicate the  dust suppressants evalu-
ated  during  this program exhibited varying  levels  of control over  the  time
                                  60

-------
    /oe
          See  Sec&en 3.4
Figure 4-1.   Average control efficiency as a function  of  time over 30 days.
                                    61

-------
period covered by runs AQ-1 to -8,  This section discusses whether there are
significant differences between  the products in terms  of  control  perfor-
mance.  In order  to  keep  the number of comparisons at a manageable level,
only TP and PM10 control efficiencies are considered.                :

     In making  interchemical  comparisons  it was first necessary to factor
out any temporal  variation.   This step was required simply because (a) it
was not possible  to  evaluate each chemical  during  each run (i.e., fewer
profilers available  than  test sections during the  first eight  tests)  and
(b) some chemicals exhibited  time-dependent  control.   For  runs  AQ-1 to -8,
normalized emission  factors were scaled by the mean (controlled) emission
factor observed during  the  test.  A two-tailed U test was then applied to
the six pairwise combinations of suppressants.  Note that a two-tailed test
was employed because there was no a priori reason to suspect that one chemi-
cal suppressant would perform "better"  than  another.   The  results  of these
comparisons for runs AQ-1 to -8 are shown below:                     :


          Chemicals                Size          Significant        ;
          compared               fraction        di fference         •

          P and G                 TP                 no
                                  PM10               no             ;

          P and S                 TP                 noj:
                                  PM10               noc            ;

          P and X                 TP                 no             ;
                                  PM10               no             ;

          G and S                 TP                 noc            j
                                  PM10               yes

          G and X                 TP                 noc            j
                                  PM10               no             :

          S and X                 TP                 yes
                                  PM10               yes            ;
          a  See caution at the end of this section.

             Two-tailed alternative hypothesis.                     :

          c  Significance levels between 5 and 10%.                 ;


     Although only  three  of the comparisons showed significant (at the 5%
level) differences in control performance, it should be noted that all com-
parisons  involving  Soil  Sement show differences at  the  10% level  of  sig-
nificance.   Only  one pairwise comparison  involving  the  other three sup-
pressants exhibited a difference significant at this level.         |
                                  62

-------
     A  final  interchemical comparison  involved the results of runs ^C"'
through -11.   After the October  rain damage, only four test sections  -*'
mained.  Because  all  suppressants were evaluated simultaneously dun>c "*
final  three  runs,  there was no need to consider temporal variation be:***"
tests.  The Friedman  test  indicated no  differences  in  either TP or  PH.- --*1"
trol at the 5% level  of significance.

     The reader is  cautioned  against the possible misuse of these  res-"** to
conclude that  one dust suppressant is "better" than another   The  re'lar**
cost-effectiveness  of each chemical is an important consideration  whe« se-
lecting a product  for use  in  a dust control  program.   For example   a 1 .>«""
priced  chemical with moderate performance characteristics may  be 'prefe?"**c
to- a highly effective yet  more expensive product in a  situation where 
-------
     The following table gives 1985 costs  for  the  dust  suppressants  evalu-
ated during the program:


                                   	Cost ($/gal)

               Suppressant

                   P
                   G
                   S
                   X
                   C
Small lot3
3.40
1.65
2.32
2.10,
0.70d
8ulkb
1.50,.
c
1,49
1,45,
0.46d
                  FOB costs for 55-gal. drums (except C).             ;
                  Data taken from MRI's cost records for the
                  field program.

                  Data developed from telephone conversations
                  with vendors and plant personnel.  All
                  prices FOB, except as noted.

               c  No plant currently produces this product.          ,'
                  See discussion in text.

                  Cost includes delivery and application.


     Because no one  currently produces generic products, definitive costs
are unavailable.  The Mellon Institute has estimated that on-site production
of this type of product would cost between $1.14 and $0.86/gal., with re-
quired capital   costs  ranging from $9,000 to  $30,000, respectively.5   The
actual cost per gallon would be a function of the production rate and would
decrease after  the  capital  costs are  recovered.   In  addition,  it may be
feasible for neighboring plants  to pool their resources  and  retain an  out-
side firm to produce the product.  Because of the variety of costs possible,
a value of  $1.15/ga1.  has  been  assigned.  This value represents  a 5<-year
average for an  annual on-site production of 20,000 gal.

     The reader should, of course, assess all costs involved in any specific
program in  which  the use of a generic product is contemplated.   The price
given above has been assigned only for the purpose of comparison.

     As a final remark about dust suppressant costs, note that the cost for
calcium chloride  includes  delivery  and application.  This fact,  combined
with a substantially lower  unit  cost,  has  resulted in some interest  in the
industry in the use of salts for unpaved road dust control.
                                  64

-------
     For runs AQ-1 through -8, the following  cost-effectiveness values were
obtained:
                                                     30-Day
                   Unit application         cost-effectiveness  rs/kol
Suppressant          costs ($/km)           TP            IP	  PM
p
G
S
X
C
1,720_
1,640C
2,150
1,720
2,190
                                            0.17          0,65        1.00    :
                                            0.15          0,64        1.03
                                            0.15          0.63        0.91    ;
                                            0.21d         0.57.       0-87.
                                            0.24a         i.iod       1.61d


3  Based on application of September  3,  1985.  Bulk costs  used with 10%     !
   increase for delivery  (except  C) and  $0.15  per gallon of concentrate
   for application.   See  discussion in text.

   Cost per kg of  emissions  reduced.  Based on 30-day average control,
   ISO vehicles per  day and  the mean, normalized  uncontrolled emission      ;
   factors in Section 3.0.

c  Assumes no delivery cost  (on-site  production).   See text for discussion
   of chemical cost.                                                        !

   Because this application  produced  a control lifetime of i»ss than  30 days,
   an average control of  50% has  been assigned.   The resulting cost-effective
   ness values should be  considered lower bounds.


     Several  remarks about  this  table are in  order.   First, the  increases   ;
over bulk costs for  delivery and application  are based on delivered prices
quoted  by consumers  and  vendors  as well as past  MRI data.1'2  Qnce again,
the  geographic location  and any  particular application requirements  for  a
plant may change  these values.   The 30-day cost-effectivenes-, values  may  be
scaled  using  other delivery  and application cost  data.

     Second,  although the road section  treated with calcium chloride  had  the
highest unit  cost, this  does not necessarily imply that this treatment  would
always  be the most  expensive.  The other  chemicals may  requi^a  storage fa-
cilities  and application equipment which could substantial]/ "increase  the
total  cost per treatment.

      For the first  test  series (AQ-1 to -8),  the cost-effect /eness values
 for calcium chloride do  not compare  favorably with those  of *ne other sup-
presants.   As noted above,  the cost-effectiveness  values  for calcium chlo-   ;
 ride may be considered lower bounds  and are between  40  and 20% higher than
 the average values  for the  other four suppressants.   However,  as  discussed
 in Section 3.4,  rainfall  during this  period was 160% of norms':  with  a total
 of 108 mm  (4.27  in.) of rain falling in  the 2 weeks between  -tins AQ-4
                                   65

-------
AQ-5.  It  is possible  that this product would  have  produced  more  favorable
cost-effectiveness values under drier conditions as was the case during runs
AQ-9 through -11.

     Cost-effectiveness values associated with runs AQ-9 through -11 are not
particularly relevant  because  weather curtailed field testing long before
an adequate description  of  decay (and, thus,  control  lifetime)  could be
obtained.  However, it is  possible to use  results  of earlier testing of
Coherex® at the  AQ  test site  to estimate  relative  cost-effectiveness  for
different application  intensities.1   Although  these earlier  tests  involved
a substantially  higher average vehicle weight, the AQ series of tests was
characterized by a higher daily traffic rate.  Assuming that  these differ-
ences balance one another suchthat the control decayand the daily emission
rates are comparable,  the following results are obtained:


                                                   30-Day average     ;
                       Unit application       	control (X)     •.
     Test series         cost ($/kni)a           TP       IP       PMin

     AQ1-8                  l»720b              47       75        73

     Reference 1            4,750C              59       72        76

     Reference 1            3,580d              93       92        94
        Developed using 1985 cost data and procedure described earlier.

        Repeat application of September 3, 1985.

     c  Initial application of 3.8 L/m2 (20% solution).

        Repeat application of 4.5 L/m2 (12% solution).


     Under the assumptions of comparable decay and emission rates, it would
appear that lighter application  intensities are more  cost-effective  over  a
30-day period, which is a fairly typical time interval between treatments in
the iron and steel industry (see Table 2-1).   This is particularly true for
the smaller particle size ranges.

4.5  EXAMINATION OF ALTERNATIVE INDICATORS OF CONTROL PERFORMANCE

     Because of  the high costs associated with conducting  field  tests of
emissions from controlled  unpaved roads,  there has been  a  great deal of
recent interest  in  developing less expensive measures of control perfor-
mance.  For example,  suppose  that a reliable estimate of a suppressant1s
effectiveness  (at a given  point in time) could be obtained by  simply ex-
amining the quantity  and/or texture of aggregrate material  present on the
road  surface.  This technique would be  an invaluable  tool to both industry
and regulatory personnel in monitoring dust control programs.        ':


                                  66

-------
     Early studies of unpaved road dust control showed a strong correlationj
between efficiency and the  silt content of  the surface material.2'12   How-
ever, it must be noted that these relationships were based on the very high.
(e.g., > 90%) control efficiencies and very low silt values typically founii
over the first few days after application.  Because these conditions repre
sent only a  small, restricted portion  of  all possible conditions,  the  high
degree of correlation is somewhat misleading.                               \

     Later study  of  long-term control  indicated no  significant  correlation
between silt content and efficiency.  In addition, fairly high (~ 50%) con
trol efficiencies were found to occur with silt contents at or above the un
controlled level.1   Because of these findings, attention turned to  the use
of the amount of silt per unit area as a performance indicator.

     Figure 4-2 presents the relationship between controlled  PM10  emission
factors (and, hence,  control efficiency)  and  silt  loading  for  Runs AQ-1
through -8.   The arrows connecting like data points denote the time history
As can  be seen,  although emission levels vary over an order of magnitude,
silt loading values vary over two orders and do not appear to follow a spe
cific trend with time.  Furthermore, the results  for the different suppres
sants tend to be  clustered  together; this would  indicate that the various
suppressant types do not affect silt loading in the same way.   The procedure
presented in Section 4.3 was used to compare silt loadings on the differeru
surfaces.   Silt loadings on the surface treated with Soil  Sement differed
from  those on  both the Coherex®  and Generic  sections at a significance
level of 5%.   In  the comparisons involving the Petro Tac surface, no sig-
nificant differences were found.

     Reasonably strong correlations between silt loading and  emissions  ap~
pear to exist for both Soil  Sement and Coherexi;  however, the two relation :
ships bear little resemblance  to one another.   For example, both products
appear  to produce essentially  the same level   of  control although the silt
loading values differ by a  factor of 50.                                   ;

     It does not  currently  appear possible  to  develop a meaningful  expres-
sion that relates the control  performance of  chemical suppressants to the
amount  of silt  loading present  on the  road  surface.  When  suppressants art-
considered individually, only Coherex® exhibits a significant correlation.
This  is not  the case,  however, when the other  petroleum  resin (Generic)  i-,
considered as well.

     Finally, it  should be  noted  that the AP-42  industrial  paved road emis
sion  factor  equation may be used  to conservatively  overestimate control lee
emissions.   This  equation  is shown in Figure  4-2,  over  the range  of  silt
loading values  in the supporting data base.   As  can be seen, the equation
tends to overestimate emissions by a  factor of 1.5 to 2 when applied to
situations with  typical  application intensities  over the  first 30 days.
Estimation is appreciably  better  for the  Soil  Sement section, possibly be-
cause the silt  loadings associated with  this  surface  more closely match
typical values  for paved roads.6  Silt loadings  for the other  three  test
sections are clustered near the  extreme value  used  in developing  the  pave-;
road equation.   As a  result, it may not be  particularly surprising that th*;
paved road equation  overestimates emissions from  these surfaces to a great*-
degree.                                                                    •

                                  67

-------
en
oo
                  10

 w
 v>
•««,

a
               O.I
                   /o
                             to
                                            ~3
to

                                                                                          0.1
/o
              Figure 4-2.  Relationship between controlled PM10 emission factors and silt  loading.

                             Arrows indicate chronology of testing.

-------
                                SECTIi,,, .
                                        >. j
                   CONTROL PERFORMANCE
                                         5E. 3EVELOPMENT
estimating the average dust control
many field tests of road dust control -
other industries,  it  is  unportant to .
only provide one estimate of average <.,
ply because the  van ous  test results
must be combined to obtain a decay rat.
base of,  say,  100  controlled tests,  v
10 pieces of information about average .
    program was  to  examine means  of
       of a suppressant.   Although
       conducted in the steel and
     that a given test series can
    efficiency.   This  is  true sim-
          times  after  application
       although  there  may be a data
 iata base may only provide,
 trol.
    Jhe following  sections  discuss t,,   .   t1tfes  of thc model  examine
previous studies of unpaved road dust .Vt°J   effectiveness  for inclusion in
the model, and, finally, present the m^,  u
S.I  OBJECTIVES OF THE AVERAGE CONTROL
                                        >CORMANCE MODEL
     It is generally conceded that th«= . ..       f  t        influence aver-
age control performance for a chemica^ •_°*up*ressant ove^ t1me;
        01rect relations hip

   Amount of chemical applied per
   unit area
   Number of previous applications
      Indirect relationship

 •rage vehicle weight
>rage number of wheels per vehicle
• ly traffic volume
     There are,  of course,  other  van's,
treated surface  aggregate,  applicatior
may  influence  average  control.  Howeve
these variables affect control and the-
draw upon.  Consequently, no attempt h&
in the model development.
  (such as the texture of the un-
' tadures or dilution ratio), that
   is not intuitively obvious how
  only  a very limited data base to
 •*«n  made to include these factors
,.   UJS  ^antageous  to  combine som, ,     /3riables shown  in the ear-
lier table.  For example, MRI's expen*,:  -    ft    a hi n intercorrelation
between  average  vehicle  weight and avfc   «       Qf wheels>   Th    as  a
first approximation, only one of the t>        --
                                  69

-------
     In addition, because of the limited data base available, it is benefi-
cial to combine traffic volume and average vehicle weight into a singpe mea-
sure of the service environment of the test road.  Let the quantity


                   /Average Weight ]    w     /Vehicles
                   I  per Vehicle   I          I per Day


be defined as  V,  the vehicle activity factor.  The data presented in Sec-
tion 2.1  show  a  mean V for  the  9  iron and steel plants of  2,400 Mg/day
(2,600 ton/day) with a 91% coefficient of variation.                 ;

     Finally, because reapplications of dust suppressants have been found to
be more effective  than  the original application, a new factor was devised
for the two variables shown as having direct relationships with average con-
trol.  This  factor,  g,  is termed the (cumulative) ground inventory and is
found by  adding  together  the total volume  (per  unit  area) of concentrate
(not solution) since the start of the dust control season.   For example, if
a plant originally applied 2 L/m2 of a 20% solution on April  1,  and followed
with 1.5  L/m2  of a 16%  solution  on the  first  of  each  following month, then
after the June 1 application, g = 0.88 L/m2.

5.2  REVIEW OF PREVIOUS STUDIES

     The first field evaluation of unpaved road dust control  in the iron and
steel industry was conducted in August 1978.  Since  that time, dozens  of
additional tests have been conducted  in the  industry; Table  5-1 summarizes
those tests.   As can be seen, several  studies entailed evaluation only a
short time after application; some tested only light-duty traffic; and still
others did not provide  enough  information on  either application parameters
or the service environment of the test road.

     The  primary selection criteria for inclusion of  data in the model  de-
velopment pertained to (a) spanning a period somewhat representative of the
time intervals in  the  iron and  steel  industry  between  applications,  and
(b) reporting the information needed for model development.

     Upon review of  controlled emission tests in the  iron and steel indus-
try, it soon became  obvious  that only petroleum  resins have  been evaluated
in enough studies to warrant an attempt at model development.  Furthermore,
this fijiding was unchanged when tests  in  other industries were consid-
ered.15 1S  As a result, only results from tests of petroleum resins in the
iron and  steel  industry are considered below.  Note that tests of generic
formulations are included with Coherex® because no significant difference
was found between the two in Section 4.3.

     Table 5-2 presents average  efficiency values for TP and PM10 control
from tests of petroleum resins in the iron and steel industry.   Correlations
are given below:
                                  70

-------
                            TABLE 5-1.   SUMMARY Of MAJOR UNPAVEO ROAD CONTROL EFFICIENCY TESTS PERFORMED AT IRON AND STEEL PLANTS


Research
organization
HRI»'2'a



Mellon
Institute* "a





EIAn..s

The main test
b .

Oust
suppressant
tested
Cohere x8
Co he rex®
Coherex®
Cohere*©
Petro T«
Cohere**
Oil well brine
flrcote 210/
Flambinder
Generic 1
Cone rex®
Generic 1
Co he rax®
CoherexD
CoheraxA
section of the road

No, of
valid
control 1 ed
tests
2
9
6
4
8
5
5
5

3
3
1
1
4
z



Test site
Araco-Mi ddl e ton
Armco-M i dd ) e ton
Armco-Kansas City
Arnco- Kansas City
J&L Indiana Harbor
Shenango
Shenango
Shenango

Shenango
Shenango
Shenango
Shenango
Shenango
US S- Homestead
was retreated 44 days after the




Measurement
method
Profiling
Profiling
Profiling
Profiling
Profiling
Upw jnd/downwind
Upw i nd/downw i nd
Upw i nd/downw 1 nd

Profiling
Profiling
Profiling
Profiling
Prof 11 ing
Profiling

Tine after
application
(days)
< 7
1-1
7-41
4-35
Z-116
3-30
3-30
3-30

3-21
3-21
9
9
Unknown
14-15

Application
intensity
(gal. iol./yd1)
Unknown
0,19
0.83 (initial)
1.0 (repaat)
0.70
1.5
3.8
1.9

O.S1 (Initial)
0.52 (initial)
0.36 (repeatr
0.36 ( repeat )c
Unknown
Unknown


Dilution ratio
(gal. chant: gal, H20)
1:9
1:6
1:4 (Initial)
1:8 (repeat)
1:4
1:4
Naat
1:4

1:9
1:9
1:12
1:12
Unknown
1:4 - 1:7


Avg. vehicle
weight (ST)
3
3-54
27-50
31-56
23-34
3
3
3

3b
3
3b
4-19
26
initial application at the Kansas City Works.





c  Road retreated 24 days after initial  application.

-------
  TABLE 5-2.   AVERAGE CONTROL EFFICIENCY FROM TESTS OF PETROLEUM RESINS3
                IN THE IRON AND STEEL INDUSTRY

Average control (%) over i
nominal period ,
V
(Mg/day)
850
2,000
2,400
3,200
3,900,
500T
2,000
2,400.
500T
g
(L/m*)
1.3
0.43
1.6
0.75
1.2
0.24.
0.4Sd
i.oa
0.23e
14-Day
TP
96b
47
98
70
95
94
59
88
89
PM10

86
99
86
96
-
60
84
<*"
30- Day
TP
90b
47
-
59
93r
87C
59

77C
PMio

73
-
76
94
_
60
-
**"
Reference
13
AQ-1 to -8
AQ-9 to -11
1
1
5
AQ-1 to -8
AQ-9 to -11
5

a  All Coherex®, except as noted.
b  TSP values.
c  Extrapolated from 21 days after application.                      ;
   Generic 2 (QS) formulation.                                        !
e  Original generic formulation.                                      :
   Assumes value of 2.7 Mg/vehicle.   Average weight not given in reference.
                                     72

-------
Size
fraction
TP
PM10
Nominal
averaging
period
14 days
30 days
14 days
30 days
Correlation of
control with
V
-0.14
0.51
-0.17
0.88
2
0.50
0.76
0.45
0.91
Sample
size
9
7
6
4
     The expected  (i.e.,  negative)  correlation between control and V was
found only in  two  cases and, in each of those cases, the degree of linear
correlation was very weak.  Because of this finding, V was dropped from con-
sideration as a model parameter.

     Additional remarks  concerning  Table 5-2 are  in  order.   The  vehicle
activity factors for Reference  5  are based on an  assumed average weight
of 2.7 Mg  (3  tons) because no  other  information was  provided.  Also, the
results from these two tests appear inconsistent with the other studies; in
fact, if the two results are deleted from the data base, average control and
V show a  very  weak,  positive correlation.  For these reasons, the results:
from Reference 5 were excluded in developing the model.                    i

5.3  AVERAGE CONTROL MODEL FOR PETROLEUM RESINS

     The data base discussed in the preceding section was used in developing
the  least-squares  models  of average control performance presented in Fig-
ure 5*1 and shown below:
                   Nominal
        Size      averaging    Sample   Estimated average  Correlation
      fracti on    ^period       si ze     efficiency (%)    coefficient

        TP        14 day         7         37 + 44 g         0.948
                  30 day         5         28 + 52 g         0.939

        PM10      14 day         6         64 + 23 g         0.755
                  30 day         4         50 + 36 g         0.915
      a  The variable "g" represents ground inventory (L/m2).  See
         text for a discussion of g.


These TP models  all  show correlations significant  at the  2% level,  while
for PM10, the corresponding level is only 10%.
                                  73

-------
      IQQ
 0



 Ui
 2
 Qe

*
I
      ICO
            \
           Q
0.5
\
I
/S
    Figure 5-1,   Average control performance model for petroleum resins.



                                      74

-------
     It is important to note that these  models  are largely designed to
typical needs in the iron and steel  industry.   The two averaging period* att*
representative of  common  time intervals  between  control  treatments in *^e
industry.  Also, the  vehicle activity factor values supporting the racers
have a mean  of  2,650 Mg/day, which  closely  matches the mean  /alue for *-1e
traffic study data presented in Section  2.1.

     How well the  model performs  for vastly different service environments
(e.g., western surface mining  or  unpaved rural  roads) is not known  at this
time.  As  a  result, the reader should be cautious when applying this  model
to situations far different than the conditions of the underlying data b
-------
                                   SECTION  6.0

                                   REFERENCES
1.  Muleski,  G.  E.,  T.  Cuscino,  Jr.,  and  C.  Cowherd, Jr.  Extended Evalua-
    tion of Onpaved  Road Dust  Suppressants In  the  Iron  and  Steel Industry,
    EPA-600/2-84-027 (NTIS  PB84-154350),  U.  S. Environmental Protection
    Agency, Research Triangle  Park, North Carolina, February 1984.

2,  Cuscino,  T., Jr., G. I.  Muleski,  and  C.  Cowherd, Jr.  Iron and Steal
    Plant Open Source Fugitive Emission Control Evaluation.  EPA-6QQ/2-83-
    110 (NTIS PB84-110568),  U. S.  Environmental Protection  Agency, Research
    Triangle Park, North Carolina, October 1983.

3.  Cowherd,  C., Jr., R. Bonn, and T. Cuscino, Jr. Iron and Steel Plant
    Open Source Fugitive Emission  Evaluation.  EPA-600/2-79-103 (NTIS
    PB299385), U. S. Environmental Protection  Agency, Research Triangle
    Park, North Carolina, May  1979.

4.  Bonn, R., T. Cuscino, Jr., and C. Cowherd, Jr. Fugitive Emissions from
    Integrated Iron  and Steel  Plants.  EPA-600/2-78-Q50 (NTIS PB281322),
    U. S. Environmental Protection Agency, Research Triangle Park, North
    Carolina, March  1978.

5.  Russell,  D., and S» C.  Caruso.  The Relative Effectiveness of a Dust
    Suppressant for  Use on  Onpaved Roads  Within ths Iron and Steel Indus-
    try.  Presented  at  SPA/AISI  Symposium on Iron  and Steel Pollution
    Abatement.  Cleveland,  Ohio, October  1984.

6.  Environmental Protection Agency.   Compilation  of Air Pollution Emission
    Factors,  Volume  I,  AP-42 (GPO  055-000-00251-7), Research Triangle Park,
    North Carolina,  September  1985.

7.  Kolnsberg, H. J. Technical  Manual for Measurement  of Fugitive Emis-
    sions:  Upwind/Downwind Sampling  Method  for Industrial  Emissions,  ;
    EPA-600/2-76-089a (NTIS PB253092), U. S. Environmental  Protection
    Agency, Research Triangle  Park, NC, April  1976.

8.  Cowherd,  C., Jr., K, Axetell,  Jr., C. M. Guenther (Maxwell), and G.
    Jutze.  Development of  Emission Factors  for Fugitive Dust Sources.
    EPA-450/3-74-037 (NTIS  PB238262), U.  S.  Environmental Protection
    Agency, Research Triangle  Park, North Carolina, June 1974,          ;

9.  Dmvies, C. N. The  Entry of  Aerosols  in  Sampling Heads  and Tubes-
    British Journal  of  Applied Physics, 2;921  (1968).                   !
                                     76

-------
10.  Muleski,  G. E,  Critical Review of Open Source Particulate Emissions
     Measurements:  Field Comparison.  MRI Final Report Prepared for Southern
     Research Institute,  MRI Project No. 7993-L(2).  August 1984.

11.  Hollander, W., and J. Wolfe.  Nonparaaetric Statistical Methods.  J
     Wiley and Sons, New York, 1973.                                        ;

12.  Cuscino,  T., Jr., G. 1. Muleski, and C. Cowherd, Jr.   Determination of
     the Decay in Control Efficiency of Chemical Dust Suppressants  on On-
     paved Roads.  Ins  Proceedings:  Symposium on Iron and Steel Pol-
     lution Abatement Technology for 1982.  SPA-600/9-33-016 (NTIS  PB83-
     258665),  0. S. Environmental Protection Agency, Research Triangle Park,
     North Carolina, April 1983, pp. 136-148.

13.  Russell D., and S. C. Caruso.  A Study of Cost-Effective Chemical Dust
     Suppressants for Use on Unpaved Roads in the Iron and Steel Industry.
     Report prepared for the American Iron and Steel Institute, December
     1982.

14.  Energy Impact Associates.  An Alternative Emission Reduction Option for
     Shenango Incorporated Coke and Iron Works, January 1981.

15.  Eoffman,  A., et al.   A Study of Controlling Fugitive  Dust Emissions
     from Nontraditional Sources at the United States Steel Corporation Fa-
     cilities in Allegheny County, Pennsylvania.  Report prepared for U. S.
     Steel Corporation, 600 Grant Street, Pittsburgh, Pennsylvania,  December
     1981.

16.  Schanche, G. W., M.  J. Savoie, J. E. Davis, V. Scarpetta, and  P. Weggel.
     Unpaved Road Dust Control Study (Ft. Carson, Colorado).  Draft Final
     Report, U. S. Army Construction Engineering Research  Laboratory,
     Champaign, Illinois, October 1981.

17.  Rosbury, K. D., and R. A. Zinuaer.  Cost-Effectiveness of Dust  Controls
     Used on Onpaved Haul Roads - Volume 1 of 2.  Draft Final Report for
     U. S. Bureau of Mines, Minneapolis, Minnesota, December 1983.

18.  Axetell, K. H., and C. Cowherd, Jr.  Improved Emission Factors for
     Fugitive Dust from Western Surface Coal Mining Sources, EPA-600/7-
     84-048 (NTIS PB84-170802), D. S. Environmental Protection Agency,
     Cincinnati, Ohio, July 1984.

19.  Cuscino, T-, Jr.  Taconite Mining Fugitive Emissions  Study. Minnesota
     Pollution Control Agency, Roseville, Minnesota, June  1979.
                                     77

-------
                                SECTION 7.0

                                 GLOSSARY
Application Frequency -  Number  of applications of a control measure to a
     specific source per  unit  time;  equivalently, the inverse of time be-
     tween two applications.

Application Intensity -  Volume  of water or chemical solution applied per
     unit area of the treated surface.

Control Efficiency, Average - Mean value of the (instantaneous)  control  ef-
     ficiency function over a specified period of time.

Control Efficiency,  (Instantaneous) - Percent decrease in controlled emis-
     sions at a given instant in time from the uncontrolled state,

Cost-Effectiveness - The  cost of  control per unit mass of reduced particu-
     late emissions.

Decay Rate - The absolute value of the slope of the (instantaneous) control
     efficiency function.

Dilution Ratio -  Ratio of the number  of parts of chemical to the  number of
     parts of solution,  expressed in percent (e.g., one part of chemical  to
     four parts of water corresponds to a 20% solution).

Dry Day - Day without measurable (0,01 in.  or more) precipitation.

Dry Sieving -  The sieving of oven-dried aggregate by passing it through a
     series of screens of descending opening size.

Oust Suppressant - Water or chemical solution which,  when applied to an ag-
     gregate material, binds suspendable particulate into larger  less sus-
     pendable particles.

Exposure - The point value of the flux (mass/area-time) of airborne particu-
     late passing  through the atmosphere,  integrated over the time  of mea-
     surement.

Exposure, Integrated - The result of  mathematical  integration of  spatially
     distributed measurements of  airborne  particulate exposure  downwind of
     a fugitive emissions source.
                                  78

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Exposure Profiling -  Direct measurement of the  total  passage  of  airborne
     participate immediately downwind of the source by means of simultaneous
     multipoint isokinetic sampling over the effective cross-section of the
     emissions plume.

Exposure Sampler - Directional particulate sampler with a fiberglass intake
     serving as a settling chamber followed by a backup filter.  The sampler
     has variable flow  control  to provide for isokinetic sampling at wind
     speeds of 1.8 to 8.9 m/s (4 to 20 mph).

Fugitive Emissions - Emissions not originating from a stack, duct, or flue.

Moisture Content - The mass portion of an aggregate sample consisting of un-
     bound surface moisture  as determined from weight  loss  in  oven drying.

Normalization - Procedure that ensures that emission reductions not attrib-
     utable to a control measure  are  excluded in determining an efficiency
     of control.

Particle Diameter, Aerodynamic -  The diameter of a hypothetical  sphere of
     ynit density (1  g/cm3)  having the same terminal settling velocity as
     the particle in question, regardless of its geometric size,  shape, and
     true density.   Units used in the report are microns aerodynamic (umA).

Particulate, Fine - Airborne particulate smaller than 2,5 urn in aerodynamic
     diameter.                                                            ;

Particulate, Inhalable - Airborne particulate smaller than 15 ym irt aerody-
     namic diameter.                                                       :

Particulate, PM10 - Airborne particulate smaller than  10 urn in aerodynamic
     diameter.                                                            :

Particulate, Total -  All airborne particulate regardless of particle size.

Particulate, Total  Suspended - Airborne particulate matter as measured by a
     standard high-volume (hi-vol) sampler.                                •

Road, Paved -  A  roadway constructed  of rigid surface  materials,  such as
     asphalt, cement,  concrete, and brick.

Road, Unpaved - A roadway constructed of nonrigid surface materials such as
     dirt,  gravel  (crushed  stone  or slag),  and oil and  chip  surfaces.

Road Surface Dust Loading,  Paved - The mass of loose surface dust on a paved
     roadway, per length of  roadway, as determined by dry vacuuming preceded
     by broom sweeping,  if necessary.

Road Surface  Oust  Loading,  Unpaved - The mass of loose surface dust on an
     unpaved  roadway,  per  unit  area, as determined by broom  sweeping.
                                  79

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Road Surface Material - Loose material present on the surface of an unpaved
     road.

Silt Content - The mass portion of an aggregate  sample  smaller than 75 mi-
     crometers in diameter as determined by dry sieving.

Silt Loading - The mass of loose surface dust per unit area on a road multi-
     plied by its silt content,                                           ;

Source, Open Dust  -  Any source from which emissions are generated by the;
     farces of wind  and  machinery acting on exposed aggregate materials.

Vehicle, Heavy-Duty - A motor vehicle with a gross vehicle travelling weight
     exceeding 30 tons.

Vehicle, Light-Duty - A motor vehicle with a gross vehicle travelling weight
     of less than or equal to 3 tons.

Vehicle, Medium-Duty  - A motor vehicle  with  a gross vehicle travelling
     weight of greater than 3 tons,  but less than 30 tons.
                                  SO

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                   SECTION 8.0



     ENGLISH TO METRIC UNIT CONVERSION TABLE

English unit Multiplied by
gal /yd2
Ib/vehicle mile
Ib
ton
mph
mile
ft
gal.
yd2
4.53
0.282
0.454
0.907
0.447
1.61
0.305
3.78
0.836
Metric unit
L/m2
kg/vehicle km
kg
Mg
tn/s
km
m
L
m2

Example:   5 miles x 1.61 = 8 km.
                     81

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                                TECHNICAL REPORT DATA
                          (Please read Instructions on the reverse before completing)
1. REPORT NO.
 EPA-600/2-87-102
                                                       3. RECIPIENT'S ACCESSION1 NO.
4, TITLS AND SU1TITLE
 Evaluation of the Effectiveness of Chemical Dust
  Suppressants on Unpaved Roads
            5. REPORT DATE
             November 1987
            6. PERFORMING ORGANIZATION CODE
7. AUTHORtS)

 G. E.  Muleski and C. Cowherd, Jr.
                                                      8. PERFORMING ORGANIZATION REPORT NO.
             8127- L (MRI)
9. PERFORMING ORGANIZATION NAME AND ADDRESS
 Midwest Research Institute
 425 Volker Boulevard
 Kansas City, Missouri  64110
                                                       10. PROGRAM ELEMENT NO.
            11. CONTRACT/GRANT NO.
              P.O. 5200-868236*
12. SPONSORING AGENCY NAME AND ADDRESS
 EPA, Office of Research and Development
 Air and Energy Engineering Research Laboratory
 Research Triangle Park, NC 27711
            13, TYPE OF REPORT AND PERIOD COVERED
              Project Report; 6/84 - 11/86
            14. SPONSORING AGENCY CODE
              EPA/600/13
is. SUPPLEMENTARY NOTES £EERL project officer is Robert C.  McCrillis, Mail Drop 62B.
 919/541-2733,, (*) LTV Steel Co.  (formerly Jones and Laughlin Steel Corp.) penalty
«. ABSTRA
              report gives results of measurements of the long-term effectiveness
 of five unpaved-road chemical dust suppressants. Effectiveness at controlling total
 particulat'e emissions in three size fractions (<15, <10,  and <2.5 micrometers)
 was determined over several cycles of chemical application, control effectiveness
 decay, and chemical reapplication. All five chemicals were tested on the same road
 with each chemical used on separate abutting road segments. The chemicals were
 applied in quantities that spanned the range of common practice in the steel indus-
 try. Traffic parameters were typical of the steel industry. Over a 30- day period,
 control effectiveness of each chemical decreased; in some cases by  as much as 50%,
 and in others by as little as  10%.  Control  effectiveness for all chemicals was > 95%
 immediately after chemical  application or reapplication. The rate of decay was
 about the same for all particle size ranges investigated.  Road surface silt loading
 was found to be a reliable indicator of relative effectiveness for some chemicals,
17.
                             KEY WORDS AND DOCUMENT ANALYSIS
                DESCRIPTORS
b. IDENTIFIERS/OPEN ENDED TERMS
c. COSATl Field/Group
 Pollution
 Dust
 Roads
 Chemical Compounds
 Iron and Steel Industry
 Pollution Control
 Stationary Sources
 Dust Suppressants
 Unpaved Roads
13B
11G    ;

07B,07C
11F
18. OISTRI1UTION STATEMENT
 Release to Public
                                          19. SECURITY CLASS {This Report)
                                           Unclassified
                         21. NO. OF PAGES
                            91
20. SECURITY CLASS (TMs page}
Unclassified
                         32, PRICE
EPA Form 2220-1 (9-73)
                                         82

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